Connect public, paid and private patent data with Google Patents Public Datasets

Document length as a static relevance feature for ranking search results

Download PDF

Info

Publication number
US9348912B2
US9348912B2 US12207910 US20791008A US9348912B2 US 9348912 B2 US9348912 B2 US 9348912B2 US 12207910 US12207910 US 12207910 US 20791008 A US20791008 A US 20791008A US 9348912 B2 US9348912 B2 US 9348912B2
Authority
US
Grant status
Grant
Patent type
Prior art keywords
search
ranking
component
query
associated
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active, expires
Application number
US12207910
Other versions
US20090106235A1 (en )
Inventor
Vladimir Tankovich
Dmitriy Meyerzon
Michael James Taylor
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Microsoft Technology Licensing LLC
Original Assignee
Microsoft Technology Licensing LLC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Grant date

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor ; File system structures therefor
    • G06F17/30861Retrieval from the Internet, e.g. browsers
    • G06F17/30864Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems

Abstract

Embodiments are configured to provide information based on a user query. In an embodiment, a system includes a search component having a ranking component that can be used to rank search results as part of a query response. In one embodiment, the ranking component includes a ranking algorithm that can use the length of documents returned in response to a search query to rank search results.

Description

RELATED APPLICATIONS

This application is a continuation-in-part of U.S. patent application Ser. No. 11/874,579, filed Oct. 18, 2007, and entitled, “RANKING AND PROVIDING SEARCH RESULTS BASED IN PART ON A NUMBER OF CLICK-THROUGH FEATURES,” which is related to U.S. patent application Ser. No. 11/874,844, filed Oct. 18, 2007, now issued U.S. Pat. No. 7,840,569, and entitled, “ENTERPRISE RELEVANCY RANKING USING A NEURAL NETWORK,” both documents hereby incorporated by reference in their entirety.

BACKGROUND

Computer users have different ways to locate information that may be locally or remotely stored. For example, search engines can be used to locate documents and other files using keywords. Search engines can also be used to perform web-based queries. A search engine attempts to return relevant results based on a query.

SUMMARY

This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended as an aid in determining the scope of the claimed subject matter.

Embodiments are configured to provide information including using one or more ranking features when providing search results. In an embodiment, a system includes a search engine that includes a ranking algorithm that can be configured to use one or more ranking features to rank and provide search results based on a query. According to one embodiment, document length may be used as a ranking feature or measure of document relevance.

These and other features and advantages will be apparent from a reading of the following detailed description and a review of the associated drawings. It is to be understood that both the foregoing general description and the following detailed description are explanatory only and are not restrictive of the invention as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a block diagram of an example system configured to manage information.

FIG. 2 is a flow diagram depicting an example of a ranking and query process.

FIG. 3 is a flow diagram depicting an example of a ranking and query process.

FIG. 4 is a block diagram illustrating a computing environment for implementation of various embodiments described herein.

DETAILED DESCRIPTION

Embodiments are configured to provide information including using one or more ranking features when providing search results. In an embodiment, a system includes a search engine that includes a ranking algorithm that can be configured to use one or more click-through ranking features to rank and provide search results based on a query. In one embodiment, a system includes a ranking component that can use a click parameter, a skip parameter, one or more stream parameters and document length to rank and provide a search result.

In one embodiment, a system includes a search component which comprises a searching application that can be included as part of a computer-readable storage medium. The searching application can be used to provide search results based in part on a user query and other user action and/or inaction. For example, a user can input keywords to the search application and the search application can use the keywords to return relevant search results. The user may or may not click on a search result for more information. As described below, the search application can use prior action and prior inaction based information when ranking and returning search results. Correspondingly, the search application can use user interactions based on a search result to provide additional focus when returning relevant search results. For example, the search application can use click-through information when ranking search results and returning the ranked search results based on a user query.

FIG. 1 is a block diagram of a system 100 which includes indexing, searching, and other functionality. For example, the system 100 can include indexing, searching, and other applications that can be used to index information as part of an indexed data structure and search for relevant data using the indexed data structure. As described below, components of the system 100 can be used to rank and return search results based at least in part on a query. For example, components of the system 100 can be configured to provide web-based search engine functionality that can be used to return search results to a user browser, based in part on a submitted query which may consist of one or more keywords, phrases, and other search items. A user can submit queries to the search component 102 using a user interface 103, such as a browser or search window for example.

As shown in FIG. 1, the system 100 includes a search component 102, such as a search engine for example, that can be configured to return results based in part on a query input. For example, the search component 102 can operate to use a word, words, phrases, concepts, and other data to locate relevant files, documents, web pages, and other information. The search component 102 can operate to locate information and can be used by an operating system (OS), file system, web-based system, or other system. The search component 102 can also be included as an add-in component, wherein the searching functionality can be used by a host system or application.

The search component 102 can be configured to provide search results (uniform resource locaters (URLs) for example) that may be associated with files, such as documents for example, file content, virtual content, web-based content, and other information. For example, the search component 102 may use text, property information, and/or metadata when returning search results associated with local files, remotely networked files, combinations of local and remote files, etc. In one embodiment, the search component 102 can interact with a file system, virtual web, network, or other information source when providing search results.

The search component 102 includes a ranking component 104 that can be configured to rank search results based at least in part on a ranking algorithm 106 and one or more ranking features 108. In one embodiment, the ranking algorithm 106 can be configured to provide a number or other variable that can be used for sorting purposes by the search component 102. The ranking features 108 can be described as basic inputs or raw numbers that can be used when identifying relevance of a search result. The ranking features 108 can be collected, stored, and maintained in a database component 110.

For example, the click-through ranking features can be stored and maintained using a number of query logging tables which can also contain query information associated with user queries. In an alternative embodiment, the ranking features 108 can be stored and maintained in a dedicated store, including local, remote, and other storage mediums. One or more of the ranking features 108 can be input to the ranking algorithm 106, and the ranking algorithm 106 can operate to rank search results as part of a ranking determination. As described below, in one embodiment, the ranking component 104 can manipulate one or more ranking features 108 as part of the ranking determination.

Correspondingly, the search component 102 can use the ranking component 104 and associated ranking algorithm 106 when using one or more of the ranking features 108 as part of a ranking determination to provide search results. Search results can be provided based on a relevance ranking or some other ranking. For example, the search component 102 can render the search results from most relevant to least relevant based at least in part on the relevance determination providing by the ranking component 104 using one or more of the ranking features 108.

With continuing reference to FIG. 1, the system 100 also includes an index component 112 that can be used to index information. The index component 112 can be used to index and catalog information to be stored in the database component 110. Moreover, the index component 102 can use the metadata, content, and/or other information when indexing against a number of disparate information sources. For example, the index component 112 can be used to build an inverted index data structure that maps keywords to documents, including URLs associated with documents.

The search component 102 can use the indexed information when returning relevant search results according to the ranking provided by the ranking component 104. In an embodiment, as part of a search, the search component 102 can be configured to identify a set of candidate results, such as a number of candidate documents for example, that contain a portion or all of a user's query information, such as keywords and phrases for example. For example, query information may be located in a document's body or metadata, or additional metadata associated with a document that can be stored in other documents or data stores (such as anchor text for example). As described below, rather than returning an entire set of search results if the set is large, the search component 102 can use the ranking component 104 to rank the candidates with respect to relevance or some other criteria, and return a subset of the entire set based at least in part on the ranking determination. However, if the set of candidates is not too large, the search component 102 can operate to return the entire set.

In an embodiment, the ranking component 104 can use the ranking algorithm 106 to predict a degree of relevance of a candidate associated with a particular query. For example, the ranking algorithm 106 can calculate a rank value associated with a candidate search result, wherein a higher rank value corresponds with a more relevant candidate. Multiple features, including one or more ranking features 108, can be input into the ranking algorithm 106 which can then compute an output that enables the search component 102 to sort candidates by a rank or some other criteria. The search component 102 can use the ranking algorithm 106 to prevent the user from having to inspect an entire set of candidates, such as large volume internet candidates and enterprise URL collections for example, by limiting a set of candidates according to rank.

In one embodiment, the search component 102 can monitor and collect action-based and/or inaction-based ranking features. The action-based and inaction-based ranking features can be stored in the database component 110 and updated as necessary. For example, click-through information, can be monitored and stored in the database component 110 as one or more ranking features 108 when a user interacts with, such as by clicking, a search result. The information can also be used to track when a user does not interact with a search result. For example, a user may skip over and not click on one or more search results. In an alternative embodiment, a separate component, such as an input detector or other recording component for example, can be used to monitor user interactions associated with a search result or results.

The search component 102 can use a select number of the collected action-based and inaction-based ranking features as part of a relevance determination when returning search results. In one embodiment, the search component 102 can collect and use a number of click-based interaction parameters as part of a relevance determination when returning search results based on a query. For example, assume that a user clicks on a search result (e.g., a document) that was not returned at the top of the results for whatever reason. As described below, the search component 102 can record and use the click feature to boost the rank of the clicked result the next time some user issues the same or a similar query. The search component 102 can also collect and use other interactive features and/or parameters, such as a touch input, pen input, and other affirmative user inputs.

In one embodiment, the search component 102 can use one or more click-through ranking features, wherein the one or more click-through ranking features can be derived from implicit user feedback. The click-through ranking features can be collected and stored, including updated features, in a number of query logging tables of the database component 110. For example, the search component 102 can use the functionality of an integrated server platform, such as MICROSOFT OFFICE SHAREPOINT SERVER® system, to collect, store, and update interaction-based features that can be used as part of a ranking determination. The functionality of the server platform can include web content management, enterprise content services, enterprise search, shared business processes, business intelligence services, and other services.

According to this embodiment, the search component 102 can use one or more click-through ranking features as part of a ranking determination when returning search results. The search component 102 can use prior click-through information when compiling the click-through ranking features which it can use to bias ranking orderings as part of a relevance determination. As described below, the one or more click-through ranking features can be used to provide a self-tunable ranking functionality by utilizing the implicit feedback a search result receives when a user interacts or does not interact with the search result. For example, a number of search results may be provided by the search component 102 listed by relevance on a search result page, and parameters can be collected based on whether the user clicks on a search result or skips a search result.

The search component 102 can use information in the database component 110, including stored action and/or inaction based features, when ranking and providing search results. The search component 102 can use query records and information associated with prior user actions or inactions associated with a query result when providing a current list of relevant results to a requestor. For example, the search component 102 can use information associated with how other users have responded to prior search results (e.g., files, documents, feeds, etc.) in response to the same or similar queries when providing a current list of references based on an issued user query.

In one embodiment, the search component 102 can be used in conjunction with the functionality of a serving system, such as the MICROSOFT OFFICE SHAREPOINT SERVER® system, operating to record and use queries and/or query strings, record and use user actions and/or inactions associated with search results, and to record and use other information associated with a relevance determination. For example, the search component 102 can be used in conjunction with the functionality of the MICROSOFT OFFICE SHAREPOINT SERVER® system, to record and use issued queries along with a search result URL that may have been clicked for a particular query. The MICROSOFT OFFICE SHAREPOINT SERVER® system can also record a list of URLs that were shown or presented with a clicked URL, such as a number of URLs that were shown above a clicked URL for example. Additionally, the MICROSOFT OFFICE SHAREPOINT SERVER® system can operate to record a search result URL that was not clicked based on a particular query. The click-through ranking features can be aggregated and used when making a relevance determination, described below.

In one embodiment, a number of click-through ranking features can be aggregated and defined as follows:

1) a click parameter, Nc, which corresponds with a number of times (across all queries) that a search result (e.g., a document, file, URL, etc.) was clicked.

2) a skip parameter, Ns, which corresponds with a number of times (across all queries) that a search result was skipped. That is, the search result was included with other search results, may have been observed by a user, but not clicked. For example, an observed or skipped search result may refer to a search result having a higher rank than a clicked result. In one embodiment, the search component 102 can use an assumption that a user scans search results from top to bottom when interacting with search results.

3) a first stream parameter, Pc, which can be represented as a text stream corresponding to a union of all query strings associated with a clicked search result. In one embodiment, the union includes all query strings for which a result was returned and clicked. Duplicates of the query strings are possible (i.e., every individual query can be used in the union operation).

4) a second stream parameter, Ps, which can be represented as a text stream corresponding to a union of all query strings associated with a skipped search result. In one embodiment, the union includes all query strings for which a result was returned and skipped. Duplicates of the query strings are possible (i.e., every individual query can be used in the union operation).

The above-listed click-through ranking features can be collected at a desired time, such as by one or more crawling systems on some periodic basis for example, and associated with each search result. For example, one or more of the click-through ranking features can be associated with a document which was returned by the search component 102 based on a user query. Thereafter, one or more of the click-through ranking features can be input to the ranking component 104 and used with the ranking algorithm 106 as part of the ranking and relevance determination. In some cases, some search results (e.g., documents, URLs, etc.) may not include click-through information. For search results with missing click-through information, certain text properties (e.g., Pc and/or Ps streams) may be left empty and certain static parameters (e.g., Nc and Ns) may have zero values.

In one embodiment, one or more of the click-through ranking features can be used with the ranking algorithm 106 which first requires collecting one or more click-through aggregates during a crawl, including full and/or incremental crawls. For example, the search component 102 can employ a crawler which can operate to crawl a file system, web-based collection, or other repository when collecting information associated with click-through ranking features and other data. One or more crawlers can be implemented for a crawl or crawls depending on the crawl target or targets and particular implementation.

The search component 102 can use the collected information, including any click-through ranking features, to update query independent stores, such as a number of query logging tables for example, with one or more features that can be used when ranking search results. For example, the search component 102 can update a number of query logging tables with the click (Nc) parameter and/or the skip (Ns) parameter for each search result that includes updated click-through information. Information associated with the updated query independent stores can be also used by various components, including the index component 102 when performing indexing operations.

Accordingly, the index component 112 can periodically obtain any changes or updates from one or more independent stores. Moreover, the index component 112 can periodically update one or more indexes which can include one or more dynamic and other features. In one embodiment, the system 100 can include two indexes, a main index and a secondary index for example, that the search component 102 can use to serve a query. The first (main) index can be used to index keywords from document bodies and/or metadata associated with web sites, file servers, and other information repositories. The secondary index can be used to index additional textual and static features that may not be directly obtained from a document. For example, additional textual and static features may include anchor text, click distance, click data, etc.

The secondary index also allows for separate update schedules. For example, when a new document is clicked, to index the associated data only requires partially rebuilding the secondary index. Thus, the main index can remain unchanged and the entire document does not require re-crawling. The main index structure can be structures as an inverted index and can be used to map keywords to document IDs, but is not so limited. For example, the index component 112 can update a secondary index using the first stream parameter Pc and/or the second stream parameter Ps for each search result that includes updated click-through information. Thereafter, one or more of the click-through ranking features and associated parameters can be applied and used by the search component 102, such as one or more inputs to the ranking algorithm 106 as part of a relevance determination associated with a query execution.

As described below, a two layer neural network can be used as part of a relevance determination. In one embodiment, the implementation of the two layer neural network includes a training phase and a ranking phase as part of a forward propagation process using the two layer neural network. A lambda ranking model can be used as a training algorithm (see C. Burges, R. Ragno, Q. V. Le, “Learning To Rank With Nonsmooth Cost Functions” in Schölkopf, Platt and Hofmann (Ed.) Advances in Neural Information Processing Systems 19, Proceedings of the 2006 Conference, (MIT Press, 2006) during the training phase, and a neural net forward propagation model can be used as part of the ranking determination. For example, a standard neural net forward propagation model can be used as part of the ranking phase. One or more of the click-through ranking features can be used in conjunction with the two layer neural network as part of a relevance determination when returning query results based on a user query.

In an embodiment, the ranking component 104 utilizes a ranking algorithm 106 which comprises a two layer neural network scoring function, hereinafter “scoring function,” which includes:

Score ( x 1 , , x n ) = ( j = 1 m h j · w 2 j ) ( 1 )

wherein,

h j = tanh ( ( i = 1 n x i · w ij ) + t j ) ( 1 a )

wherein,

hj is an output of hidden node j,

xi is an input value from input node i, such as one or more ranking feature inputs,

w2j is a weight to be applied to a hidden node output,

wij is a weight to be applied to input value xi by hidden node j,

tj is the threshold value for hidden node j,

and, tan h is the hyperbolic tangent function:

h j = tanh ( ( i = 1 n x i · w ij ) + t j ) ( 1 c )

In an alternative embodiment, other functions having similar properties and characteristics as the tan h function can be used above. In one embodiment, the variable xi can represent one or more click-through parameters. A λ-rank training algorithm can be used to train the two layer neural network scoring function before ranking as part of a relevance determination. Moreover, new features and parameters can be added to the scoring function without significantly affecting a training accuracy or training speed.

One or more ranking features 108 can be input and used by the ranking algorithm 106, the two layer neural network scoring function for this embodiment, when making a relevance determination when returning search results based on a user query. In one embodiment, one or more click-through ranking parameters (Nc, Ns, Pc, and/or Ps can be input and used by the ranking algorithm 106 when making a relevance determination as part of returning search results based on a user query.

The Nc parameter can be used to produce an additional input to the two layer neural net scoring function. In one embodiment, the input value associated with the Nc parameter can be calculated according to the following formula:

input = x iN c = ( N c K Nc + N c - M Nc ) S Nc ( 2 )

wherein,

in one embodiment, the Nc parameter corresponds with a raw parameter value associated with a number of times (across all queries and all users) that a search result was clicked.

KNc is a tunable parameter (e.g., greater than or equal to zero).

MNc and SNc are mean and standard deviation parameters or normalization constants associated with training data, and,

iNc corresponds with an index of an input mode.

The Ns parameter can be used to produce an additional input to the two layer neural net scoring function. In one embodiment, the input value associated with the Ns parameter can be calculated according to the following formula:

input = x iN s = ( N s K Ns + N s - M Ns ) S Ns ( 3 )

wherein,

in one embodiment, the Ns parameter corresponds with a raw parameter value associated with a number of times (across all queries and all users) that a search result was skipped.

KNs is a tunable parameter (e.g., greater than or equal to zero),

MNs and SNs are mean and standard deviation parameters or normalization constants associated with training data, and,

iNs corresponds with an index of an input node.

The Pc parameter can be incorporated into the formula (4) below which can be used to produce a content dependent input to the two layer neural net scoring function.

input = x iBM 25 main = BM 25 G main ( Q , D ) = ( ( t Q TF t k 1 + TF t · log ( N n t ) ) - M ) S ( 4 )

The formula for TF′t can be calculated as follows:

TF t = ( p D \ Pc TF t , p · w p · 1 + b p ( DL p AVDL p + b p ) ) + TF t , Pc · w Pc · 1 + b pc ( DL Pc AVDL Pc + b Pc ) ( 5 )

wherein,

Q is a query string,

t is an individual query term (e.g., word),

D is a result (e.g., document) being scored,

p is an individual property of a result (e.g., document) (for example, title, body, anchor text, author, etc. and any other textual property to be used for ranking,

N is a total number of results (e.g., documents) in a search domain,

nt is a number of results (e.g., documents) containing term t,

DLp is a length of the property p,

AVDLp is an average length of the property p,

TFt,p is a term t frequency in the property p,

TFt,pc corresponds to a number of times that a given term appears in the parameter Pc,

DLpc corresponds with a length of the parameter Pc (e.g., the number of terms included),

AVDLpc corresponds with an average length of the parameter Pc,

wpc and bpc correspond with tunable parameters,

D\Pc corresponds with a set of properties of a document D excluding property Pc (item for Pc is taken outside of the sum sign only for clarity),

iBM25main is an index of an input node, and,

M and S represent mean and standard deviation normalization constants.

The Ps parameter can be incorporated into the formula (6) below which can be used to produce an additional input to the two layer neural net scoring function.

input = x iP s = BM 25 G secondary ( Q , D ) = ( ( t Q TF t k 1 + TF t · log ( N n t ) ) - M ) S ( 6 )

where,

TF t - TF t , p s · w p s · 1 + b p s ( DL p s AVDL p s + b p s ) ( 7 )

and,

TFt,ps represent a number of times that a given term is associated with the Ps parameter,

DLps represents a length of the Ps parameter (e.g., a number of terms),

AVDLps represents an average length of the Ps parameter,

N represents a number of search results (e.g., documents) in a corpus,

nt represents a number of search results (e.g., documents) containing a given query term,

k′s, wPs, bPs represent tunable parameters, and,

M and S represent mean and standard deviation normalization constants.

Once one or more of the inputs have been calculated as shown above, one or more of the inputs can be input into (1), and a score or ranking can be output which can then be used when ranking search results as part of the relevance determination. As an example, x1 can be used to represent the calculated input associated with the Nc parameter, x2 can be used to represent the calculated input associated with the Ns parameter, x3 can be used to represent the calculated input associated with the Pc parameter, and, x4 can be used to represent the calculated input associated with the Ps parameter. As described above, streams can also include body, title, author, URL, anchor text, generated title, and/or Pc. Accordingly, one or more inputs, e.g., x1, x2, x3, and/or x4 can be input into the scoring function (1) when ranking search results as part of the relevance determination. Correspondingly, the search component 102 can provide ranked search results to a user based on an issued query and one or more ranking inputs. For example, the search component 102 can return a set of URLs, wherein URLs within the set can be presented to the user based on a ranking order (e.g., high relevance value to low relevance value).

Other features can also be used when ranking and providing search results. In an embodiment, click distance (CD), URL depth (UD), file type or type prior (T), language or language prior (L), and/or other ranking features can be used to rank and provide search results. One or more of the additional ranking features can be used as part of a linear ranking determination, neural net determination, or other ranking determination. For example, one or more static ranking features can be used in conjunction with one or more dynamic ranking features as part of a linear ranking determination, neural net determination, or other ranking determination.

Accordingly, CD represents click distance, wherein CD can be described as a query-independent ranking feature that measures a number of “clicks” required to reach a given target, such as a page or document for example, from a reference location. CD takes advantage of a hierarchical structure of a system which may follow a tree structure, with a root node (e.g., the homepage) and subsequent branches extending to other nodes from that root. Viewing the tree as a graph, CD may be represented as the shortest path between the root, as reference location, and the given page. UD represents URL depth, wherein UD can be used to represent a count of the number of slashes (“/”) in a URL. T represents type prior, and, L represents language prior.

The T and L features can be used to represent enumerated data types. Examples of such a data type include file type and language type. As an example, for any given search domain, there may be a finite set of file types present and/or supported by the associated search engine. For example an enterprise intranet may contain word processing documents, spreadsheets, HTML web pages, and other documents. Each of these file types may have a different impact on the relevance of the associated document. An exemplary transformation can convert a file type value into a set of binary flags, one for each supported file type. Each of these flags can be used by a neural network individually so that each may be given a separate weight and processed separately. Language (in which the document is written) can be handled in a similar manner, with a single discrete binary flag used to indicate whether or not a document is written in a certain language. The sum of the term frequencies may also include body, title, author, anchor text, URL display name, extracted title, etc.

Ultimately, user satisfaction is one of surest measures of the operation of the search component 102. A user would prefer that the search component 102 quickly return the most relevant results, so that the user is not required to invest much time investigating a resulting set of candidates. For example, a metric evaluation can be used to determine a level of user satisfaction. In one embodiment, a metric evaluation can be improved by varying inputs to the ranking algorithm 106 or aspects of the ranking algorithm 106. A metric evaluation can be computed over some representative or random set of queries. For example, a representative set of queries can be selected based on a random sampling of queries contained in query logs stored in the database component 110. Relevance labels can be assigned to or associated with each result returned by the search component 102 for each of the metric evaluation queries.

For example, a metric evaluation may comprise an average count of relevant documents in the query at top N (1, 5, 10, etc.) results (also referred to as precision @ 1, 5, 10, etc.). As another example, a more complicated measure can be used to evaluate search results, such as an average precision or Normalized Discounted Cumulative Gain (NDCG). The NDCG can be described as a cumulative metric that allows multi-level judgments and penalizes the search component 102 for returning less relevant documents higher in the rank, and more relevant documents lower in the rank. A metric can be averaged over a query set to determine an overall accuracy quantification.

Continuing the NDCG example, for a given query “Qi” the NDCG can be computed as:

M q j = 1 N ( 2 r ( f ) - 1 ) / log ( 1 + f ) ( 8 )

where N is typically 3 or 10. The metric can be averaged over a query set to determine an overall accuracy number.

Below are some experimental results obtained based on using the Nc, Ns, and Pc click-through parameters with the scoring function (1). Experiments were conducted on 10-splits query set (744 queries, ˜130K documents), 5-fold cross-validation run. For each fold, 6 splits were used for training, 2 for validation, and 2 for testing. A standard version of a λ-rank algorithm was used (see above).

Accordingly, aggregated results using 2-layer neural net scoring function with 4 hidden nodes resulted in the following as shown in Table 1 below:

TABLE 1
Set of features NDCG@1 NDCG@3 NDCG@10
Baseline (no click- 62.841 60.646 62.452
through features)
Incorporated Nc, Ns 64.598 62.237 63.164
and Pc (+2.8%) (+2.6%) (+1.1%)

The aggregated results using 2-layer neural net scoring function with 6 hidden nodes resulted in the following as shown in Table 2 below:

TABLE 2
Set of features NDCG@1 NDCG@3 NDCG@10
Baseline (no click- 62.661 60.899 62.373
through)
Incorporated Nc, Ns 65.447 62.515 63.296
and Pc (+4.4%) (+2.7%) (+1.5%)

One additional ranking feature 108 that can be used as a measure of document relevance is document length. Document length may be an effective ranking tool because short documents typically do not include enough information to be useful for a user. That is, short documents typically do not provide an answer to a search query. On the other hand, large documents typically include so much information that is sometimes difficult to determine what information in the document is related to the search query.

Since many different types of documents may be returned as a result of a search query, a first step in determining document rank is to compute a normalized value of document length. This is done to make document length independent of the type of documents that are ranked. The normalized length of a document is defined as being equal to the length of a document, in words, divided by the average length of the set of documents being ranked, for example the documents returned as a result of a search query. This can be represented by the following equation:
D=L D /L AVG  (9)

, where D represents the normalized document length, LD represent the length of the document being ranked, and LAVG represents the average length of documents in a set of documents.

A transform function is then used to provide a ranking value, from zero to one, for the normalized document length, a higher ranking value representing a more relevant document. In one embodiment, the transform function can be represented as follows:
F(D)=D,D<=1  (10)
F(D)=0.5+(3−D)/4,1<D<=3  (11)
F(D)=2/(D+1),D>3  (12)

This example transform function penalizes documents for being too long or too short. The highest ranking value of one is computed for a document of average length, i.e, for a document having a normalized length of one. By contrast, a document with a normalized length of 0.5 (i.e half the average length) has a ranking value of 0.5 and a document with a normalized length of seven (i.e seven times the average length) has a ranking value of 0.25.

The document length ranking values can be stored in the database component 110 and updated as necessary. The search component 102 can use the document length information in the database component 110 when ranking and providing search results.

FIG. 2 is a flow diagram illustrating a process of providing information based in part on a user query, in accordance with an embodiment. Components of FIG. 1 are used in the description of FIG. 2, but the embodiment is not so limited. At 200, the search component 102 receives query data associated with a user query. For example, a user using a web-based browser can submit a text string consisting of a number of keywords which defines the user query. At 202, the search component 102 can communicate with the database component 110 to retrieve any ranking features 108 associated with the user query. For example, the search component 102 can retrieve one or more click-through ranking features from a number of query tables, wherein the one or more click-through ranking features are associated with previously issued queries having similar or identical keywords.

At 204, the search component 102 can use the user query to locate one or more search results. For example, the search component 102 can use a text string to locate documents, files, and other data structures associated with a file system, database, web-based collection, or some other information repository. At 206, the search component 102 uses one or more of the ranking features 108 to rank the search results. For example, the search component 102 can input one or more click-through ranking parameters to the scoring function (1) which can provide an output associated with a ranking for each search result.

At 208, the search component 102 can use the rankings to provide the search results to a user in a ranked order. For example, the search component 102 can provide a number of retrieved documents to a user, wherein the retrieved documents can be presented to the user according to a numerical ranking order (e.g., a descending order, ascending order, etc.). At 210, the search component 102 can use a user action or inaction associated with a search result to update one or more ranking features 108 which may be stored in the database component 110. For example, if a user clicked or skipped a URL search result, the search component 102 can push the click-through data (click data or skip data) to a number of query logging tables of the database component 110. Thereafter, the index component 112 can operate to use the updated ranking features for various indexing operations, including indexing operations associated with updating an indexed catalog of information.

FIG. 3 is a flow diagram illustrating a process of providing information based in part on a user query, in accordance with an embodiment. Again, components of FIG. 1 are used in the description of FIG. 3, but the embodiment is not so limited. The process of FIG. 3 is subsequent to the search component 102 receiving a user query issued from the user interface 103, wherein the search component 102 has located a number of documents which satisfy the user query. For example, the search component 102 can use a number of submitted keywords to locate documents as part of a web-based search.

At 300, the search component 102 obtains a next document which satisfied the user query. If all documents have been located by the search component 102 at 302, the flow proceeds to 316, wherein the search component 102 can sort the located documents according to rank. If all documents have not been located at 302, the flow proceeds to 304 and the search component 102 retrieves any click-through features from the database component 110, wherein the retrieved click-through features are associated with the current document located by the search component 102.

At 306, the search component 102 can compute an input associated with the Pc parameter for use by the scoring function (1) as part of a ranking determination. For example, the search component 102 can input the Pc parameter into the formula (4) to compute an input associated with the Pc parameter. At 308, the search component 102 can compute a second input associated with the Nc parameter for use by the scoring function (1) as part of a ranking determination. For example, the search component 102 can input the Nc parameter into the formula (2) to compute an input associated with the Nc parameter.

At 310, the search component 102 can compute a third input associated with the Ns parameter for use by the scoring function (1) as part of a ranking determination. For example, the search component 102 can input the Ns parameter into the formula (3) to compute an input associated with the Ns parameter. At 312, the search component 102 can compute a fourth input associated with the Ps parameter for use by the scoring function (1) as part of a ranking determination. For example, the search component 102 can input the Ps parameter into the formula (6) to compute an input associated with the Ps parameter.

At 313, the search component 102 can compute a fifth input associated with document length for use by the scoring function (1) as part of a ranking determination. For example, the search component 102 can compute the number of words in each document obtained as a result of the user query, the number of words in each document being representative of the length of that document. The normalized length of each document can be obtained using the formula (9) by dividing the length of each document by the average length of all documents obtained as a result of the query. A ranking value based on document length can then be obtained using the transform function defined by the formulas (10), (11) and (12) to compute a ranking value having a range between zero and one.

At 314, the search component 102 operates to input one or more of the calculated inputs into the scoring function (1) to compute a rank for the current document. In alternative embodiments, the search component 102 may instead calculate input values associated with select parameters, rather than calculating inputs for each click-through parameter. If there are no remaining documents to rank, at 316 the search component 102 sorts the documents by rank. For example, the search component 102 may sort the documents according to a descending rank order, starting with a document having a highest rank value and ending with a document having a lowest rank value. The search component 102 can also use the ranking as a cutoff to limit the number of results presented to the user. For example, the search component 102 may only present documents having a rank greater than X, when providing search results. Thereafter, the search component 102 can provide the sorted documents to a user for further action or inaction. While a certain order is described with respect to FIGS. 2 and 3, the order can be changed according to a desired implementation.

The embodiments and examples described herein are not intended to be limiting and other embodiments are available. Moreover, the components described above can be implemented as part of networked, distributed, or other computer-implemented environment. The components can communicate via a wired, wireless, and/or a combination of communication networks. A number of client computing devices, including desktop computers, laptops, handhelds, or other smart devices can interact with and/or be included as part of the system 100.

In alternative embodiments, the various components can be combined and/or configured according to a desired implementation. For example, the index component 112 can be included with the search component 102 as a single component for providing indexing and searching functionality. As additional example, neural networks can be implemented either in hardware or software. While certain embodiments include software implementations, they are not so limited and they encompass hardware, or mixed hardware/software solutions. Other embodiments and configurations are available.

Exemplary Operating Environment

Referring now to FIG. 4, the following discussion is intended to provide a brief, general description of a suitable computing environment in which embodiments of the invention may be implemented. While the invention will be described in the general context of program modules that execute in conjunction with program modules that run on an operating system on a personal computer, those skilled in the art will recognize that the invention may also be implemented in combination with other types of computer systems and program modules.

Generally, program modules include routines, programs, components, data structures, and other types of structures that perform particular tasks or implement particular abstract data types. Moreover, those skilled in the art will appreciate that the invention may be practiced with other computer system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers, and the like. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

Referring now to FIG. 4, an illustrative operating environment for embodiments of the invention will be described. As shown in FIG. 4, computer 2 comprises a general purpose desktop, laptop, handheld, or other type of computer capable of executing one or more application programs. The computer 2 includes at least one central processing unit 8 (“CPU”), a system memory 12, including a random access memory 18 (“RAM”) and a read-only memory (“ROM”) 20, and a system bus 10 that couples the memory to the CPU 8. A basic input/output system containing the basic routines that help to transfer information between elements within the computer, such as during startup, is stored in the ROM 20. The computer 2 further includes a mass storage device 14 for storing an operating system 32, application programs, and other program modules.

The mass storage device 14 is connected to the CPU 8 through a mass storage controller (not shown) connected to the bus 10. The mass storage device 14 and its associated computer-readable media provide non-volatile storage for the computer 2. Although the description of computer-readable media contained herein refers to a mass storage device, such as a hard disk or CD-ROM drive, it should be appreciated by those skilled in the art that computer-readable media can be any available media that can be accessed or utilized by the computer 2.

By way of example, and not limitation, computer-readable media may comprise computer storage media and communication media. Computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EPROM, EEPROM, flash memory or other solid state memory technology, CD-ROM, digital versatile disks (“DVD”), or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by the computer 2.

According to various embodiments of the invention, the computer 2 may operate in a networked environment using logical connections to remote computers through a network 4, such as a local network, the Internet, etc. for example. The computer 2 may connect to the network 4 through a network interface unit 16 connected to the bus 10. It should be appreciated that the network interface unit 16 may also be utilized to connect to other types of networks and remote computing systems. The computer 2 may also include an input/output controller 22 for receiving and processing input from a number of other devices, including a keyboard, mouse, etc. (not shown). Similarly, an input/output controller 22 may provide output to a display screen, a printer, or other type of output device.

As mentioned briefly above, a number of program modules and data files may be stored in the mass storage device 14 and RAM 18 of the computer 2, including an operating system 32 suitable for controlling the operation of a networked personal computer, such as the WINDOWS operating systems from MICROSOFT CORPORATION of Redmond, Wash. The mass storage device 14 and RAM 18 may also store one or more program modules. In particular, the mass storage device 14 and the RAM 18 may store application programs, such as a search application 24, word processing application 28, a spreadsheet application 30, e-mail application 34, drawing application, etc.

It should be appreciated that various embodiments of the present invention can be implemented (1) as a sequence of computer implemented acts or program modules running on a computing system and/or (2) as interconnected machine logic circuits or circuit modules within the computing system. The implementation is a matter of choice dependent on the performance requirements of the computing system implementing the invention. Accordingly, logical operations including related algorithms can be referred to variously as operations, structural devices, acts or modules. It will be recognized by one skilled in the art that these operations, structural devices, acts and modules may be implemented in software, firmware, special purpose digital logic, and any combination thereof without deviating from the spirit and scope of the present invention as recited within the claims set forth herein.

Although the invention has been described in connection with various exemplary embodiments, those of ordinary skill in the art will understand that many modifications can be made thereto within the scope of the claims that follow. Accordingly, it is not intended that the scope of the invention in any way be limited by the above description, but instead be determined entirely by reference to the claims that follow.

Claims (19)

What is claimed is:
1. A system for providing information comprising:
one or more processors;
one or more computer storage media storing computer executable instructions that when executed by the one or more processors provide:
a search component configured to locate a search result based on a query input;
a database component configured to store information associated with the query input including one or more ranking features, wherein the one or more ranking features are associated with a user action or user inaction associated with the search result which are collected with respect to the search result for a same query or a similar query previously received, and wherein one ranking feature of the one or more ranking features is associated with a normalized document length wherein the normalized document length is determined by dividing a length of a document to be ranked by an average length of a set of documents included in the search result, wherein the document to be ranked is included in the set of documents, wherein the length of the document corresponds to a number of words in the document; and
a ranking component configured to rank the search result based, at least in part, on a ranking function and the one or more ranking features, including an action-based feature, an inaction-based feature and a normalized document length feature, wherein the search component uses the rank of the search result when providing search results according to a ranking order.
2. The system of claim 1, wherein a transform function converts the normalized document length into a ranking value between zero and one.
3. The system of claim 2, wherein the transform function is defined as:

F(D)=D,D<=1

F(D)=0.5+(3−D)/4,1<B<=3

F(D)=2/(D+1),D>3,
wherein, D represents the normalized document length and F(D) represents the ranking value.
4. The system of claim 1, wherein the ranking component uses one or more click-through parameters when ranking the search result, wherein the one or more click-through parameters further comprise one or more of the following:
a click parameter associated with a number of times that the search result has been clicked;
a skip parameter associated with a number of times that the search result has been skipped;
a first stream parameter corresponding to a union of query strings associated with a clicked search result; and
a second stream parameter corresponding to a union of query strings associated with a skipped search result.
5. The system of claim 4, wherein the search component is further configured to update the one or more click-through parameters including using information associated with how the search result was interacted with when updating the one or more of the click-through parameters.
6. The system of claim 5, wherein the search component is further configured to update the one or more click-through parameters, wherein the update of the one or more click-through parameters corresponds with a selected search result or a skipped search result.
7. The system of claim 1, wherein the wherein the one or more ranking features comprise one or more dynamic ranking features selected from a group consisting of body, title, author, generated title, an anchor text, and a URL, and one or more static ranking features selected from a group consisting of click distance, URL depth, file type, and language.
8. A non-transitory computer-readable storage medium storing computer executable instructions that when executed by one or more processors provide a search engine configured to:
receive information associated with a query;
locate a search result associated with the query, wherein the search result includes one or more documents;
calculate a first input associated with a click parameter and the search result;
calculate a second input associated with a skip parameter and the search result;
calculate a third input associated with a normalized document length of the one or more documents included in the search result, wherein the normalized document length of the one or more documents is obtained by dividing a length of each document of the one or more documents by an average length of each document of the one or more documents included in the search result, wherein the length of the document corresponds to a number of words in the document; wherein the length of the document corresponds to a number of words in the document;
store information associated with the query including one or more ranking features, wherein the one or more ranking features are associated with a user action or user inaction associated with the search result which are collected with respect to the search result for a same query or a similar query previously received, and wherein one ranking feature of the one or more ranking features is associated with a normalized document length, wherein the document to be ranked is included in the one or more documents;
ranking the search result based on a ranking determination using the ranking features, the first input, the second input, and the third input;
and provide the search result according to the ranking determination.
9. The non-transitory computer-readable storage medium of claim 8, further configured to
calculate a fourth input associated with a first stream parameter and the search result;
calculate a fifth input associated with a second stream parameter and the search result; and
rank the one or more documents included in the search result using at least four of the first input, the second input, the third input, the fourth input, and the fifth input.
10. The non-transitory computer-readable storage medium of claim 8, further configured to update a store with click parameter and skip parameter updates associated with received interactions with the one or more documents included in the search result.
11. The non-transitory computer-readable storage medium of claim 8, further configured to update a store with stream parameter updates associated with received interactions with the one or more documents included in the search result.
12. A method of providing information comprising:
searching to locate a search result based on a query input;
storing information associated with the query input including one or more ranking features, wherein the one or more ranking features are associated with a user action or user inaction associated with the search result which are collected with respect to the search result for a same query or a similar query previously received, and wherein one ranking feature of the one or more ranking features is associated with a normalized document length wherein the normalized document length is determined by dividing a length of a document to be ranked by an average length of a set of documents included in the search result, wherein the document to be ranked is included in the set of documents, wherein the length of the document corresponds to a number of words in the document; and
ranking the search result based, at least in part, on a ranking function and the one or more ranking features, including an action-based feature, an inaction-based feature and a normalized document length feature, wherein the search component uses the rank of the search result when providing search results according to a ranking order.
13. The method of claim 12, further comprising:
determining a fourth input value associated with a text stream and a received selection of at least one of the one or more query candidates; and
ranking the one or more query candidates based in part on a scoring determination using a scoring function and one or more of the first input value, the second input value, the third input value and the fourth input value.
14. The method of claim 12, further comprising ranking the one or more query candidates according to a numerical order.
15. The system of claim 1, wherein the normalized document length is determined independently from a file type of one or more documents included in the search result.
16. The non-transitory computer-readable storage medium of claim 8, wherein the normalized document length of the one or more documents included in the search result is determined independently from a file type of the one or more documents included in the search result.
17. The non-transitory computer-readable storage medium of claim 8, wherein the normalized document length of the one or more documents is obtained by dividing a length of each document of the one or more documents by an average length of each document of the one or more documents included in the search result.
18. The method of claim 12, wherein the normalized document length of the at least one of the query candidates is determined independently from a file type of the at least one of the query candidates.
19. The method of claim 12, wherein the normalized document length of the at least one of the query candidates is obtained by dividing a length of the at least one of the query candidates by an average length of the one or more query candidates included in a result of the query.
US12207910 2007-10-18 2008-09-10 Document length as a static relevance feature for ranking search results Active 2029-09-17 US9348912B2 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
US11874579 US20090106221A1 (en) 2007-10-18 2007-10-18 Ranking and Providing Search Results Based In Part On A Number Of Click-Through Features
US12207910 US9348912B2 (en) 2007-10-18 2008-09-10 Document length as a static relevance feature for ranking search results

Applications Claiming Priority (6)

Application Number Priority Date Filing Date Title
US12207910 US9348912B2 (en) 2007-10-18 2008-09-10 Document length as a static relevance feature for ranking search results
RU2011108842A RU2517271C2 (en) 2008-09-10 2009-11-05 Document length as relevancy statistic id for search results ranging
EP20090813811 EP2329411A4 (en) 2008-09-10 2009-11-05 Document length as a static relevance feature for ranking search results
KR20117005588A KR101683311B1 (en) 2008-09-10 2009-11-05 A method, system and computer-readable storage medium for providing information by using document length as a static relevance feature for ranking search results
JP2011527079A JP5620913B2 (en) 2008-09-10 2009-11-05 Document length of as a static-related properties for the ranking of search results
PCT/US2009/063333 WO2010031085A3 (en) 2008-09-10 2009-11-05 Document length as a static relevance feature for ranking search results

Related Parent Applications (1)

Application Number Title Priority Date Filing Date
US11874579 Continuation-In-Part US20090106221A1 (en) 2007-10-18 2007-10-18 Ranking and Providing Search Results Based In Part On A Number Of Click-Through Features

Publications (2)

Publication Number Publication Date
US20090106235A1 true US20090106235A1 (en) 2009-04-23
US9348912B2 true US9348912B2 (en) 2016-05-24

Family

ID=42005833

Family Applications (1)

Application Number Title Priority Date Filing Date
US12207910 Active 2029-09-17 US9348912B2 (en) 2007-10-18 2008-09-10 Document length as a static relevance feature for ranking search results

Country Status (6)

Country Link
US (1) US9348912B2 (en)
JP (1) JP5620913B2 (en)
KR (1) KR101683311B1 (en)
EP (1) EP2329411A4 (en)
RU (1) RU2517271C2 (en)
WO (1) WO2010031085A3 (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160162467A1 (en) * 2014-12-09 2016-06-09 Idibon, Inc. Methods and systems for language-agnostic machine learning in natural language processing using feature extraction

Families Citing this family (23)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7606793B2 (en) 2004-09-27 2009-10-20 Microsoft Corporation System and method for scoping searches using index keys
US7761448B2 (en) 2004-09-30 2010-07-20 Microsoft Corporation System and method for ranking search results using click distance
US7827181B2 (en) * 2004-09-30 2010-11-02 Microsoft Corporation Click distance determination
US7716198B2 (en) * 2004-12-21 2010-05-11 Microsoft Corporation Ranking search results using feature extraction
US20060200460A1 (en) * 2005-03-03 2006-09-07 Microsoft Corporation System and method for ranking search results using file types
US7792833B2 (en) * 2005-03-03 2010-09-07 Microsoft Corporation Ranking search results using language types
US20120130814A1 (en) * 2007-11-14 2012-05-24 Paul Vincent Hayes System and method for search engine result ranking
US9348912B2 (en) 2007-10-18 2016-05-24 Microsoft Technology Licensing, Llc Document length as a static relevance feature for ranking search results
US7917503B2 (en) * 2008-01-17 2011-03-29 Microsoft Corporation Specifying relevance ranking preferences utilizing search scopes
US8812493B2 (en) 2008-04-11 2014-08-19 Microsoft Corporation Search results ranking using editing distance and document information
US8041710B2 (en) * 2008-11-13 2011-10-18 Microsoft Corporation Automatic diagnosis of search relevance failures
US20110137886A1 (en) * 2009-12-08 2011-06-09 Microsoft Corporation Data-Centric Search Engine Architecture
US8738635B2 (en) 2010-06-01 2014-05-27 Microsoft Corporation Detection of junk in search result ranking
US9098569B1 (en) * 2010-12-10 2015-08-04 Amazon Technologies, Inc. Generating suggested search queries
US8694507B2 (en) 2011-11-02 2014-04-08 Microsoft Corporation Tenantization of search result ranking
US9495462B2 (en) 2012-01-27 2016-11-15 Microsoft Technology Licensing, Llc Re-ranking search results
US20130262966A1 (en) * 2012-04-02 2013-10-03 Industrial Technology Research Institute Digital content reordering method and digital content aggregator
US8972399B2 (en) * 2012-06-22 2015-03-03 Microsoft Technology Licensing, Llc Ranking based on social activity data
US9237386B2 (en) 2012-08-31 2016-01-12 Google Inc. Aiding discovery of program content by providing deeplinks into most interesting moments via social media
US9401947B1 (en) * 2013-02-08 2016-07-26 Google Inc. Methods, systems, and media for presenting comments based on correlation with content
US20150100570A1 (en) * 2013-10-09 2015-04-09 Foxwordy, Inc. Excerpted Content
WO2016017001A1 (en) * 2014-07-31 2016-02-04 楽天株式会社 Search device, search method, recording medium, and program
US9720774B2 (en) * 2015-06-29 2017-08-01 Sap Se Adaptive recovery for SCM-enabled databases

Citations (382)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6182065B2 (en)
JPS62297950A (en) 1986-06-13 1987-12-25 Ibm Journaling of data system
US5222236A (en) 1988-04-29 1993-06-22 Overdrive Systems, Inc. Multiple integrated document assembly data processing system
US5257577A (en) 1991-04-01 1993-11-02 Clark Melvin D Apparatus for assist in recycling of refuse
US5321833A (en) 1990-08-29 1994-06-14 Gte Laboratories Incorporated Adaptive ranking system for information retrieval
US5369778A (en) 1987-08-21 1994-11-29 Wang Laboratories, Inc. Data processor that customizes program behavior by using a resource retrieval capability
US5544360A (en) 1992-11-23 1996-08-06 Paragon Concepts, Inc. Method for accessing computer files and data, using linked categories assigned to each data file record on entry of the data file record
US5594660A (en) 1994-09-30 1997-01-14 Cirrus Logic, Inc. Programmable audio-video synchronization method and apparatus for multimedia systems
US5606609A (en) 1994-09-19 1997-02-25 Scientific-Atlanta Electronic document verification system and method
US5634124A (en) 1987-08-21 1997-05-27 Wang Laboratories, Inc. Data integration by object management
US5729730A (en) 1995-03-28 1998-03-17 Dex Information Systems, Inc. Method and apparatus for improved information storage and retrieval system
JPH1091638A (en) 1996-09-17 1998-04-10 Toshiba Corp Search system
US5765150A (en) 1996-08-09 1998-06-09 Digital Equipment Corporation Method for statistically projecting the ranking of information
JPH10240757A (en) 1997-02-27 1998-09-11 Hitachi Ltd Cooperative decentralized retrieval system
US5826269A (en) 1995-06-21 1998-10-20 Microsoft Corporation Electronic mail interface for a network server
US5828999A (en) * 1996-05-06 1998-10-27 Apple Computer, Inc. Method and system for deriving a large-span semantic language model for large-vocabulary recognition systems
US5848404A (en) 1997-03-24 1998-12-08 International Business Machines Corporation Fast query search in large dimension database
US5870740A (en) 1996-09-30 1999-02-09 Apple Computer, Inc. System and method for improving the ranking of information retrieval results for short queries
US5870739A (en) 1996-09-20 1999-02-09 Novell, Inc. Hybrid query apparatus and method
US5890147A (en) 1997-03-07 1999-03-30 Microsoft Corporation Scope testing of documents in a search engine using document to folder mapping
US5893092A (en) 1994-12-06 1999-04-06 University Of Central Florida Relevancy ranking using statistical ranking, semantics, relevancy feedback and small pieces of text
US5893116A (en) 1996-09-30 1999-04-06 Novell, Inc. Accessing network resources using network resource replicator and captured login script for use when the computer is disconnected from the network
US5905866A (en) 1996-04-30 1999-05-18 A.I. Soft Corporation Data-update monitoring in communications network
US5913210A (en) 1998-03-27 1999-06-15 Call; Charles G. Methods and apparatus for disseminating product information via the internet
US5920859A (en) 1997-02-05 1999-07-06 Idd Enterprises, L.P. Hypertext document retrieval system and method
US5933851A (en) 1995-09-29 1999-08-03 Sony Corporation Time-stamp and hash-based file modification monitor with multi-user notification and method thereof
US5933822A (en) 1997-07-22 1999-08-03 Microsoft Corporation Apparatus and methods for an information retrieval system that employs natural language processing of search results to improve overall precision
US5943670A (en) 1997-11-21 1999-08-24 International Business Machines Corporation System and method for categorizing objects in combined categories
JPH11232300A (en) 1998-02-18 1999-08-27 Nri & Ncc Co Ltd Browsing client server system
RU2138076C1 (en) 1998-09-14 1999-09-20 Закрытое акционерное общество "МедиаЛингва" Data retrieval system in computer network
US5956722A (en) 1997-09-23 1999-09-21 At&T Corp. Method for effective indexing of partially dynamic documents
US5960383A (en) 1997-02-25 1999-09-28 Digital Equipment Corporation Extraction of key sections from texts using automatic indexing techniques
US5983216A (en) 1997-09-12 1999-11-09 Infoseek Corporation Performing automated document collection and selection by providing a meta-index with meta-index values indentifying corresponding document collections
US5987457A (en) 1997-11-25 1999-11-16 Acceleration Software International Corporation Query refinement method for searching documents
JPH11328191A (en) 1998-05-13 1999-11-30 Nec Corp Www robot retrieving system
US6006225A (en) 1998-06-15 1999-12-21 Amazon.Com Refining search queries by the suggestion of correlated terms from prior searches
US6012053A (en) 1997-06-23 2000-01-04 Lycos, Inc. Computer system with user-controlled relevance ranking of search results
US6026398A (en) 1997-10-16 2000-02-15 Imarket, Incorporated System and methods for searching and matching databases
US6029164A (en) 1997-06-16 2000-02-22 Digital Equipment Corporation Method and apparatus for organizing and accessing electronic mail messages using labels and full text and label indexing
US6032196A (en) 1995-12-13 2000-02-29 Digital Equipment Corporation System for adding a new entry to a web page table upon receiving a web page including a link to another web page not having a corresponding entry in the web page table
US6038610A (en) 1996-07-17 2000-03-14 Microsoft Corporation Storage of sitemaps at server sites for holding information regarding content
US6041323A (en) * 1996-04-17 2000-03-21 International Business Machines Corporation Information search method, information search device, and storage medium for storing an information search program
US6070158A (en) 1996-08-14 2000-05-30 Infoseek Corporation Real-time document collection search engine with phrase indexing
US6070191A (en) 1997-10-17 2000-05-30 Lucent Technologies Inc. Data distribution techniques for load-balanced fault-tolerant web access
JP2000194713A (en) 1998-12-25 2000-07-14 Nippon Telegr & Teleph Corp <Ntt> Method and device for retrieving character string, and storage medium stored with character string retrieval program
US6098064A (en) 1998-05-22 2000-08-01 Xerox Corporation Prefetching and caching documents according to probability ranked need S list
US6115709A (en) 1998-09-18 2000-09-05 Tacit Knowledge Systems, Inc. Method and system for constructing a knowledge profile of a user having unrestricted and restricted access portions according to respective levels of confidence of content of the portions
US6125361A (en) 1998-04-10 2000-09-26 International Business Machines Corporation Feature diffusion across hyperlinks
US6128701A (en) 1997-10-28 2000-10-03 Cache Flow, Inc. Adaptive and predictive cache refresh policy
US6145003A (en) 1997-12-17 2000-11-07 Microsoft Corporation Method of web crawling utilizing address mapping
US6151624A (en) 1998-02-03 2000-11-21 Realnames Corporation Navigating network resources based on metadata
US6167369A (en) 1998-12-23 2000-12-26 Xerox Company Automatic language identification using both N-gram and word information
US6167402A (en) 1998-04-27 2000-12-26 Sun Microsystems, Inc. High performance message store
US6178419B1 (en) 1996-07-31 2001-01-23 British Telecommunications Plc Data access system
US6182067B1 (en) 1997-06-02 2001-01-30 Knowledge Horizons Pty Ltd. Methods and systems for knowledge management
US6182113B1 (en) 1997-09-16 2001-01-30 International Business Machines Corporation Dynamic multiplexing of hyperlinks and bookmarks
US6182085B1 (en) 1998-05-28 2001-01-30 International Business Machines Corporation Collaborative team crawling:Large scale information gathering over the internet
US6182065B1 (en) 1996-11-06 2001-01-30 International Business Machines Corp. Method and system for weighting the search results of a database search engine
US6185558B1 (en) 1998-03-03 2001-02-06 Amazon.Com, Inc. Identifying the items most relevant to a current query based on items selected in connection with similar queries
JP2001052017A (en) 1999-08-11 2001-02-23 Fuji Xerox Co Ltd Hypertext analyzer
US6199081B1 (en) 1998-06-30 2001-03-06 Microsoft Corporation Automatic tagging of documents and exclusion by content
US6202058B1 (en) 1994-04-25 2001-03-13 Apple Computer, Inc. System for ranking the relevance of information objects accessed by computer users
US6208988B1 (en) 1998-06-01 2001-03-27 Bigchalk.Com, Inc. Method for identifying themes associated with a search query using metadata and for organizing documents responsive to the search query in accordance with the themes
US6216123B1 (en) 1998-06-24 2001-04-10 Novell, Inc. Method and system for rapid retrieval in a full text indexing system
US6222559B1 (en) 1996-10-02 2001-04-24 Nippon Telegraph And Telephone Corporation Method and apparatus for display of hierarchical structures
JP2001117934A (en) 1999-10-19 2001-04-27 Hitachi Ltd Method and system for managing electronic document and recording medium
US6240408B1 (en) 1998-06-08 2001-05-29 Kcsl, Inc. Method and system for retrieving relevant documents from a database
US6247013B1 (en) 1997-06-30 2001-06-12 Canon Kabushiki Kaisha Hyper text reading system
US6263364B1 (en) 1999-11-02 2001-07-17 Alta Vista Company Web crawler system using plurality of parallel priority level queues having distinct associated download priority levels for prioritizing document downloading and maintaining document freshness
US6269370B1 (en) 1996-02-21 2001-07-31 Infoseek Corporation Web scan process
US6272507B1 (en) 1997-04-09 2001-08-07 Xerox Corporation System for ranking search results from a collection of documents using spreading activation techniques
US6285999B1 (en) * 1997-01-10 2001-09-04 The Board Of Trustees Of The Leland Stanford Junior University Method for node ranking in a linked database
US6285367B1 (en) 1998-05-26 2001-09-04 International Business Machines Corporation Method and apparatus for displaying and navigating a graph
JP2001265774A (en) 2000-03-16 2001-09-28 Nippon Telegr & Teleph Corp <Ntt> Method and device for retrieving information, recording medium with recorded information retrieval program and hypertext information retrieving system
US6304864B1 (en) 1999-04-20 2001-10-16 Textwise Llc System for retrieving multimedia information from the internet using multiple evolving intelligent agents
US6314421B1 (en) 1998-05-12 2001-11-06 David M. Sharnoff Method and apparatus for indexing documents for message filtering
US6317741B1 (en) 1996-08-09 2001-11-13 Altavista Company Technique for ranking records of a database
US20010042076A1 (en) 1997-06-30 2001-11-15 Ryoji Fukuda A hypertext reader which performs a reading process on a hierarchically constructed hypertext
US6324551B1 (en) 1998-08-31 2001-11-27 Xerox Corporation Self-contained document management based on document properties
US6326962B1 (en) 1996-12-23 2001-12-04 Doubleagent Llc Graphic user interface for database system
US6327590B1 (en) 1999-05-05 2001-12-04 Xerox Corporation System and method for collaborative ranking of search results employing user and group profiles derived from document collection content analysis
US6336117B1 (en) 1999-04-30 2002-01-01 International Business Machines Corporation Content-indexing search system and method providing search results consistent with content filtering and blocking policies implemented in a blocking engine
DE10029644A1 (en) 2000-06-16 2002-01-17 Deutsche Telekom Ag Hypertext documents evaluation method using search engine, involves calculating real relevance value for each document based on precalculated relevance value and cross references of document
JP2002024015A (en) 2000-07-11 2002-01-25 Misawa Van Corp Method for constructing client server system
US20020016787A1 (en) * 2000-06-28 2002-02-07 Matsushita Electric Industrial Co., Ltd. Apparatus for retrieving similar documents and apparatus for extracting relevant keywords
US6349308B1 (en) 1998-02-25 2002-02-19 Korea Advanced Institute Of Science & Technology Inverted index storage structure using subindexes and large objects for tight coupling of information retrieval with database management systems
US6351755B1 (en) 1999-11-02 2002-02-26 Alta Vista Company System and method for associating an extensible set of data with documents downloaded by a web crawler
US6351467B1 (en) 1997-10-27 2002-02-26 Hughes Electronics Corporation System and method for multicasting multimedia content
US20020026390A1 (en) 2000-08-25 2002-02-28 Jonas Ulenas Method and apparatus for obtaining consumer product preferences through product selection and evaluation
KR20020015838A (en) 2000-08-23 2002-03-02 전홍건 Method for re-adjusting ranking of document to use user's profile and entropy
US20020032772A1 (en) 2000-09-14 2002-03-14 Bjorn Olstad Method for searching and analysing information in data networks
US6360215B1 (en) 1998-11-03 2002-03-19 Inktomi Corporation Method and apparatus for retrieving documents based on information other than document content
JP2002091843A (en) 2000-09-11 2002-03-29 Nippon Telegr & Teleph Corp <Ntt> Device and method for selecting server and recording medium recording server selection program
US6381597B1 (en) 1999-10-07 2002-04-30 U-Know Software Corporation Electronic shopping agent which is capable of operating with vendor sites which have disparate formats
US6385602B1 (en) 1998-11-03 2002-05-07 E-Centives, Inc. Presentation of search results using dynamic categorization
US20020055940A1 (en) 2000-11-07 2002-05-09 Charles Elkan Method and system for selecting documents by measuring document quality
JP2002132769A (en) 2000-10-25 2002-05-10 Nippon Telegr & Teleph Corp <Ntt> Method and device for multilateral retrieval service and recording medium recording program therefor
US6389436B1 (en) 1997-12-15 2002-05-14 International Business Machines Corporation Enhanced hypertext categorization using hyperlinks
JP2002140365A (en) 2000-11-01 2002-05-17 Mitsubishi Electric Corp Data retrieving method
US20020062323A1 (en) 2000-11-20 2002-05-23 Yozan Inc Browser apparatus, server apparatus, computer-readable medium, search system and search method
US20020078045A1 (en) 2000-12-14 2002-06-20 Rabindranath Dutta System, method, and program for ranking search results using user category weighting
US20020083054A1 (en) 2000-12-27 2002-06-27 Kyle Peltonen Scoping queries in a search engine
US6415319B1 (en) 1997-02-07 2002-07-02 Sun Microsystems, Inc. Intelligent network browser using incremental conceptual indexer
US6418453B1 (en) 1999-11-03 2002-07-09 International Business Machines Corporation Network repository service for efficient web crawling
US6418452B1 (en) 1999-11-03 2002-07-09 International Business Machines Corporation Network repository service directory for efficient web crawling
US6418433B1 (en) 1999-01-28 2002-07-09 International Business Machines Corporation System and method for focussed web crawling
JP2002202992A (en) 2000-12-28 2002-07-19 Speed System:Kk Homepage retrieval system
US6424966B1 (en) 1998-06-30 2002-07-23 Microsoft Corporation Synchronizing crawler with notification source
US20020099694A1 (en) 2000-11-21 2002-07-25 Diamond Theodore George Full-text relevancy ranking
US20020103798A1 (en) 2001-02-01 2002-08-01 Abrol Mani S. Adaptive document ranking method based on user behavior
US20020107861A1 (en) 2000-12-07 2002-08-08 Kerry Clendinning System and method for collecting, associating, normalizing and presenting product and vendor information on a distributed network
US20020107886A1 (en) 2001-02-07 2002-08-08 Gentner Donald R. Method and apparatus for automatic document electronic versioning system
US6442606B1 (en) 1999-08-12 2002-08-27 Inktomi Corporation Method and apparatus for identifying spoof documents
JP2002245089A (en) 2001-02-19 2002-08-30 Hitachi Eng Co Ltd Web page retrieval system, secondary information collecting device and interface unit
US20020123988A1 (en) 2001-03-02 2002-09-05 Google, Inc. Methods and apparatus for employing usage statistics in document retrieval
US20020129015A1 (en) 2001-01-18 2002-09-12 Maureen Caudill Method and system of ranking and clustering for document indexing and retrieval
US20020129014A1 (en) 2001-01-10 2002-09-12 Kim Brian S. Systems and methods of retrieving relevant information
US6473752B1 (en) 1997-12-04 2002-10-29 Micron Technology, Inc. Method and system for locating documents based on previously accessed documents
US20020165873A1 (en) * 2001-02-22 2002-11-07 International Business Machines Corporation Retrieving handwritten documents using multiple document recognizers and techniques allowing both typed and handwritten queries
US20020169754A1 (en) 2001-05-08 2002-11-14 Jianchang Mao Apparatus and method for adaptively ranking search results
US20020169800A1 (en) 2001-01-05 2002-11-14 International Business Machines Corporation XML: finding authoritative pages for mining communities based on page structure criteria
US20020169770A1 (en) 2001-04-27 2002-11-14 Kim Brian Seong-Gon Apparatus and method that categorize a collection of documents into a hierarchy of categories that are defined by the collection of documents
US20020169595A1 (en) 2001-03-30 2002-11-14 Yevgeny Agichtein Method for retrieving answers from an information retrieval system
US20020168106A1 (en) 2001-05-11 2002-11-14 Miroslav Trajkovic Palette-based histogram matching with recursive histogram vector generation
US6484204B1 (en) 1997-05-06 2002-11-19 At&T Corp. System and method for allocating requests for objects and managing replicas of objects on a network
JP2002366549A (en) 2001-05-07 2002-12-20 Nec Corp Selective retrieval metasearch engine and method for performing selective retrieval
US20030004952A1 (en) 1999-10-18 2003-01-02 Mark Nixon Accessing and updating a configuration database from distributed physical locations within a process control system
US6516312B1 (en) 2000-04-04 2003-02-04 International Business Machine Corporation System and method for dynamically associating keywords with domain-specific search engine queries
EP1282060A2 (en) 2001-08-03 2003-02-05 Overture Services, Inc. System and method for providing place and price protection in a search result list generated by a computer network search engine
US20030028520A1 (en) 2001-06-20 2003-02-06 Alpha Shamim A. Method and system for response time optimization of data query rankings and retrieval
US20030037074A1 (en) 2001-05-01 2003-02-20 Ibm Corporation System and method for aggregating ranking results from various sources to improve the results of web searching
US6526440B1 (en) 2001-01-30 2003-02-25 Google, Inc. Ranking search results by reranking the results based on local inter-connectivity
US20030046389A1 (en) 2001-09-04 2003-03-06 Thieme Laura M. Method for monitoring a web site's keyword visibility in search engines and directories and resulting traffic from such keyword visibility
JP2003067419A (en) 2001-08-24 2003-03-07 Toshiba Corp Information retrieving method and information retrieval system
JP2003076715A (en) 2001-08-20 2003-03-14 Nhn Corp Method and system for retrieving web pages, program and recording medium
US20030053084A1 (en) 2001-07-19 2003-03-20 Geidl Erik M. Electronic ink as a software object
US20030055810A1 (en) 2001-09-18 2003-03-20 International Business Machines Corporation Front-end weight factor search criteria
US6539376B1 (en) 1999-11-15 2003-03-25 International Business Machines Corporation System and method for the automatic mining of new relationships
US20030061201A1 (en) 2001-08-13 2003-03-27 Xerox Corporation System for propagating enrichment between documents
US20030065706A1 (en) 2001-05-10 2003-04-03 Smyth Barry Joseph Intelligent internet website with hierarchical menu
US6546388B1 (en) 2000-01-14 2003-04-08 International Business Machines Corporation Metadata search results ranking system
US6549896B1 (en) 2000-04-07 2003-04-15 Nec Usa, Inc. System and method employing random walks for mining web page associations and usage to optimize user-oriented web page refresh and pre-fetch scheduling
US6547829B1 (en) 1999-06-30 2003-04-15 Microsoft Corporation Method and system for detecting duplicate documents in web crawls
US6549897B1 (en) 1998-10-09 2003-04-15 Microsoft Corporation Method and system for calculating phrase-document importance
US20030074368A1 (en) 1999-01-26 2003-04-17 Hinrich Schuetze System and method for quantitatively representing data objects in vector space
US6553364B1 (en) 1997-11-03 2003-04-22 Yahoo! Inc. Information retrieval from hierarchical compound documents
US6557036B1 (en) 1999-07-20 2003-04-29 Sun Microsystems, Inc. Methods and apparatus for site wide monitoring of electronic mail systems
US6560600B1 (en) 2000-10-25 2003-05-06 Alta Vista Company Method and apparatus for ranking Web page search results
US20030088545A1 (en) 2001-06-18 2003-05-08 Pavitra Subramaniam System and method to implement a persistent and dismissible search center frame
US20030101183A1 (en) 2001-11-26 2003-05-29 Navin Kabra Information retrieval index allowing updating while in use
US6594682B2 (en) 1997-10-28 2003-07-15 Microsoft Corporation Client-side system for scheduling delivery of web content and locally managing the web content
US20030135490A1 (en) 2002-01-15 2003-07-17 Barrett Michael E. Enhanced popularity ranking
US6598047B1 (en) 1999-07-26 2003-07-22 David W. Russell Method and system for searching text
US6598040B1 (en) 2000-08-14 2003-07-22 International Business Machines Corporation Method and system for processing electronic search expressions
US6598051B1 (en) 2000-09-19 2003-07-22 Altavista Company Web page connectivity server
JP2003208434A (en) 2001-11-07 2003-07-25 Nec Corp Information retrieval system, and information retrieval method using the same
US6601075B1 (en) 2000-07-27 2003-07-29 International Business Machines Corporation System and method of ranking and retrieving documents based on authority scores of schemas and documents
JP2003248696A (en) 2002-02-22 2003-09-05 Nippon Telegr & Teleph Corp <Ntt> Page rating/filtering method, device, and program, and computer readable recording medium recording the program
US6622140B1 (en) 2000-11-15 2003-09-16 Justsystem Corporation Method and apparatus for analyzing affect and emotion in text
US6628304B2 (en) 1998-12-09 2003-09-30 Cisco Technology, Inc. Method and apparatus providing a graphical user interface for representing and navigating hierarchical networks
US6631369B1 (en) 1999-06-30 2003-10-07 Microsoft Corporation Method and system for incremental web crawling
US6633868B1 (en) 2000-07-28 2003-10-14 Shermann Loyall Min System and method for context-based document retrieval
US6633867B1 (en) 2000-04-05 2003-10-14 International Business Machines Corporation System and method for providing a session query within the context of a dynamic search result set
US20030195882A1 (en) 2002-04-11 2003-10-16 Lee Chung Hee Homepage searching method using similarity recalculation based on URL substring relationship
US6636853B1 (en) 1999-08-30 2003-10-21 Morphism, Llc Method and apparatus for representing and navigating search results
KR20030082109A (en) 2002-04-16 2003-10-22 (주)메타웨이브 Method and System for Providing Information and Retrieving Index Word using AND Operator
US6638314B1 (en) 1998-06-26 2003-10-28 Microsoft Corporation Method of web crawling utilizing crawl numbers
WO2003009180A3 (en) 2001-07-19 2003-11-06 Computer Ass Think Inc Method and system for reorganizing a tablespace in a database
US20030217052A1 (en) 2000-08-24 2003-11-20 Celebros Ltd. Search engine method and apparatus
US20030217007A1 (en) 2002-01-29 2003-11-20 Sony Corporation Method for providing and obtaining content
US20030217047A1 (en) 1999-03-23 2003-11-20 Insightful Corporation Inverse inference engine for high performance web search
US6654742B1 (en) 1999-02-12 2003-11-25 International Business Machines Corporation Method and system for document collection final search result by arithmetical operations between search results sorted by multiple ranking metrics
US20040003028A1 (en) 2002-05-08 2004-01-01 David Emmett Automatic display of web content to smaller display devices: improved summarization and navigation
US20040006559A1 (en) 2002-05-29 2004-01-08 Gange David M. System, apparatus, and method for user tunable and selectable searching of a database using a weigthted quantized feature vector
US6678692B1 (en) 2000-07-10 2004-01-13 Northrop Grumman Corporation Hierarchy statistical analysis system and method
JP2004021589A (en) 2002-06-17 2004-01-22 Nec System Technologies Ltd Internet information retrieval system
US20040024752A1 (en) 2002-08-05 2004-02-05 Yahoo! Inc. Method and apparatus for search ranking using human input and automated ranking
JP2004054588A (en) 2002-07-19 2004-02-19 Just Syst Corp Document retrieval device and method and program for making computer execute the same method
US6701318B2 (en) 1998-11-18 2004-03-02 Harris Corporation Multiple engine information retrieval and visualization system
US20040049766A1 (en) 2002-09-09 2004-03-11 Bloch Joshua J. Method and apparatus for associating metadata attributes with program elements
US20040064442A1 (en) 2002-09-27 2004-04-01 Popovitch Steven Gregory Incremental search engine
US6718365B1 (en) 2000-04-13 2004-04-06 International Business Machines Corporation Method, system, and program for ordering search results using an importance weighting
US20040093328A1 (en) 2001-02-08 2004-05-13 Aditya Damle Methods and systems for automated semantic knowledge leveraging graph theoretic analysis and the inherent structure of communication
JP2004164555A (en) 2002-09-17 2004-06-10 Fuji Xerox Co Ltd Apparatus and method for retrieval, and apparatus and method for index building
US20040117351A1 (en) 2002-12-14 2004-06-17 International Business Machines Corporation System and method for identifying and utilizing a secondary index to access a database using a management system without an internal catalogue of online metadata
JP2004192657A (en) 2004-02-09 2004-07-08 Nec Corp Information retrieval system, and recording medium recording information retrieval method and program for information retrieval
US6763362B2 (en) 2001-11-30 2004-07-13 Micron Technology, Inc. Method and system for updating a search engine
US6766422B2 (en) 2001-09-27 2004-07-20 Siemens Information And Communication Networks, Inc. Method and system for web caching based on predictive usage
US20040141354A1 (en) 2003-01-18 2004-07-22 Carnahan John M. Query string matching method and apparatus
US20040148278A1 (en) 2003-01-22 2004-07-29 Amir Milo System and method for providing content warehouse
US6772141B1 (en) 1999-12-14 2004-08-03 Novell, Inc. Method and apparatus for organizing and using indexes utilizing a search decision table
US6775659B2 (en) 1998-08-26 2004-08-10 Symtec Limited Methods and devices for mapping data files
US6775664B2 (en) 1996-04-04 2004-08-10 Lycos, Inc. Information filter system and method for integrated content-based and collaborative/adaptive feedback queries
US20040181515A1 (en) 2003-03-13 2004-09-16 International Business Machines Corporation Group administration of universal resource identifiers with members identified in search result
RU2236699C1 (en) 2003-02-25 2004-09-20 Открытое акционерное общество "Телепортал. Ру" Method for searching and selecting information with increased relevance
US20040186827A1 (en) 2003-03-21 2004-09-23 Anick Peter G. Systems and methods for interactive search query refinement
JP2004265015A (en) 2003-02-28 2004-09-24 Toyota Infotechnology Center Co Ltd Content-retrieving index generation device
US20040194099A1 (en) 2003-03-31 2004-09-30 John Lamping System and method for providing preferred language ordering of search results
US20040199497A1 (en) 2000-02-08 2004-10-07 Sybase, Inc. System and Methodology for Extraction and Aggregation of Data from Dynamic Content
US20040205497A1 (en) 2001-10-22 2004-10-14 Chiang Alexander System for automatic generation of arbitrarily indexed hyperlinked text
CA2279119C (en) 1999-07-29 2004-10-19 Ibm Canada Limited-Ibm Canada Limitee Heuristic-based conditional data indexing
US20040215664A1 (en) 1999-03-31 2004-10-28 Microsoft Corporation Method for promoting contextual information to display pages containing hyperlinks
US6829606B2 (en) 2002-02-14 2004-12-07 Infoglide Software Corporation Similarity search engine for use with relational databases
US20040249795A1 (en) 2003-06-05 2004-12-09 International Business Machines Corporation Semantics-based searching for information in a distributed data processing system
US20040254932A1 (en) 2003-06-16 2004-12-16 Vineet Gupta System and method for providing preferred country biasing of search results
US20040260695A1 (en) 2003-06-20 2004-12-23 Brill Eric D. Systems and methods to tune a general-purpose search engine for a search entry point
US20040267722A1 (en) 2003-06-30 2004-12-30 Larimore Stefan Isbein Fast ranked full-text searching
US20050033742A1 (en) 2003-03-28 2005-02-10 Kamvar Sepandar D. Methods for ranking nodes in large directed graphs
US6859800B1 (en) 2000-04-26 2005-02-22 Global Information Research And Technologies Llc System for fulfilling an information need
US20050044071A1 (en) 2000-06-08 2005-02-24 Ingenuity Systems, Inc. Techniques for facilitating information acquisition and storage
US6862710B1 (en) 1999-03-23 2005-03-01 Insightful Corporation Internet navigation using soft hyperlinks
US20050055340A1 (en) 2002-07-26 2005-03-10 Brainbow, Inc. Neural-based internet search engine with fuzzy and learning processes implemented by backward propogation
US20050055347A9 (en) 2000-12-08 2005-03-10 Ingenuity Systems, Inc. Method and system for performing information extraction and quality control for a knowledgebase
US6868411B2 (en) 2001-08-13 2005-03-15 Xerox Corporation Fuzzy text categorizer
US20050060186A1 (en) 2003-08-28 2005-03-17 Blowers Paul A. Prioritized presentation of medical device events
US20050060311A1 (en) 2003-09-12 2005-03-17 Simon Tong Methods and systems for improving a search ranking using related queries
US20050060310A1 (en) 2003-09-12 2005-03-17 Simon Tong Methods and systems for improving a search ranking using population information
US20050060304A1 (en) 2002-11-19 2005-03-17 Prashant Parikh Navigational learning in a structured transaction processing system
US6873982B1 (en) 1999-07-16 2005-03-29 International Business Machines Corporation Ordering of database search results based on user feedback
US20050071741A1 (en) 2003-09-30 2005-03-31 Anurag Acharya Information retrieval based on historical data
US20050071328A1 (en) 2003-09-30 2005-03-31 Lawrence Stephen R. Personalization of web search
US6883135B1 (en) 2000-01-28 2005-04-19 Microsoft Corporation Proxy server using a statistical model
US20050086192A1 (en) 2003-10-16 2005-04-21 Hitach, Ltd. Method and apparatus for improving the integration between a search engine and one or more file servers
US20050086206A1 (en) 2003-10-15 2005-04-21 International Business Machines Corporation System, Method, and service for collaborative focused crawling of documents on a network
US6886010B2 (en) 2002-09-30 2005-04-26 The United States Of America As Represented By The Secretary Of The Navy Method for data and text mining and literature-based discovery
US6886129B1 (en) 1999-11-24 2005-04-26 International Business Machines Corporation Method and system for trawling the World-wide Web to identify implicitly-defined communities of web pages
US20050089215A1 (en) 2003-10-25 2005-04-28 Carl Staelin Image artifact reduction using a neural network
US20050114324A1 (en) 2003-09-14 2005-05-26 Yaron Mayer System and method for improved searching on the internet or similar networks and especially improved MetaNews and/or improved automatically generated newspapers
US20050125392A1 (en) 2003-12-08 2005-06-09 Andy Curtis Methods and systems for providing a response to a query
US6910029B1 (en) 2000-02-22 2005-06-21 International Business Machines Corporation System for weighted indexing of hierarchical documents
US20050144162A1 (en) 2003-12-29 2005-06-30 Ping Liang Advanced search, file system, and intelligent assistant agent
US20050154710A1 (en) 2004-01-08 2005-07-14 International Business Machines Corporation Dynamic bitmap processing, identification and reusability
US20050154746A1 (en) 2004-01-09 2005-07-14 Yahoo!, Inc. Content presentation and management system associating base content and relevant additional content
EP1557770A1 (en) 2004-01-23 2005-07-27 Microsoft Corporation Building and using subwebs for focused search
US20050165718A1 (en) 2004-01-26 2005-07-28 Fontoura Marcus F. Pipelined architecture for global analysis and index building
US20050165781A1 (en) 2004-01-26 2005-07-28 Reiner Kraft Method, system, and program for handling anchor text
US6931397B1 (en) 2000-02-11 2005-08-16 International Business Machines Corporation System and method for automatic generation of dynamic search abstracts contain metadata by crawler
US6934714B2 (en) 2002-03-04 2005-08-23 Intelesis Engineering, Inc. Method and system for identification and maintenance of families of data records
US20050192955A1 (en) 2004-03-01 2005-09-01 International Business Machines Corporation Organizing related search results
US20050192936A1 (en) 2004-02-12 2005-09-01 Meek Christopher A. Decision-theoretic web-crawling and predicting web-page change
US6944609B2 (en) 2001-10-18 2005-09-13 Lycos, Inc. Search results using editor feedback
US20050210105A1 (en) 2004-03-22 2005-09-22 Fuji Xerox Co., Ltd. Conference information processing apparatus, and conference information processing method and storage medium readable by computer
US20050210079A1 (en) 2004-03-17 2005-09-22 Edlund Stefan B Method for synchronizing documents for disconnected operation
US20050210006A1 (en) 2004-03-18 2005-09-22 Microsoft Corporation Field weighting in text searching
US20050216533A1 (en) 2004-03-29 2005-09-29 Yahoo! Inc. Search using graph colorization and personalized bookmark processing
US6959326B1 (en) 2000-08-24 2005-10-25 International Business Machines Corporation Method, system, and program for gathering indexable metadata on content at a data repository
US20050240580A1 (en) 2003-09-30 2005-10-27 Zamir Oren E Personalization of placed content ordering in search results
US20050251499A1 (en) 2004-05-04 2005-11-10 Zezhen Huang Method and system for searching documents using readers valuation
US20050256865A1 (en) 2004-05-14 2005-11-17 Microsoft Corporation Method and system for indexing and searching databases
US20050262050A1 (en) 2004-05-07 2005-11-24 International Business Machines Corporation System, method and service for ranking search results using a modular scoring system
US6973490B1 (en) 1999-06-23 2005-12-06 Savvis Communications Corp. Method and system for object-level web performance and analysis
US20050283473A1 (en) 2004-06-17 2005-12-22 Armand Rousso Apparatus, method and system of artificial intelligence for data searching applications
US20050289193A1 (en) 2004-06-25 2005-12-29 Yan Arrouye Methods and systems for managing data
US20050289133A1 (en) 2004-06-25 2005-12-29 Yan Arrouye Methods and systems for managing data
US20060004732A1 (en) 2002-02-26 2006-01-05 Odom Paul S Search engine methods and systems for generating relevant search results and advertisements
US6990628B1 (en) 1999-06-14 2006-01-24 Yahoo! Inc. Method and apparatus for measuring similarity among electronic documents
US20060031183A1 (en) 2004-08-04 2006-02-09 Tolga Oral System and method for enhancing keyword relevance by user's interest on the search result documents
US6999959B1 (en) 1997-10-10 2006-02-14 Nec Laboratories America, Inc. Meta search engine
US20060036598A1 (en) 2004-08-09 2006-02-16 Jie Wu Computerized method for ranking linked information items in distributed sources
US7003442B1 (en) 1998-06-24 2006-02-21 Fujitsu Limited Document file group organizing apparatus and method thereof
US20060041521A1 (en) 2004-08-04 2006-02-23 Tolga Oral System and method for providing graphical representations of search results in multiple related histograms
US20060047649A1 (en) 2003-12-29 2006-03-02 Ping Liang Internet and computer information retrieval and mining with intelligent conceptual filtering, visualization and automation
US20060047643A1 (en) 2004-08-31 2006-03-02 Chirag Chaman Method and system for a personalized search engine
US7010532B1 (en) 1997-12-31 2006-03-07 International Business Machines Corporation Low overhead methods and apparatus for shared access storage devices
US20060059144A1 (en) 2004-09-16 2006-03-16 Telenor Asa Method, system, and computer program product for searching for, navigating among, and ranking of documents in a personal web
US7016540B1 (en) 1999-11-24 2006-03-21 Nec Corporation Method and system for segmentation, classification, and summarization of video images
US20060064411A1 (en) 2004-09-22 2006-03-23 William Gross Search engine using user intent
US20060069982A1 (en) 2004-09-30 2006-03-30 Microsoft Corporation Click distance determination
US20060074883A1 (en) 2004-10-05 2006-04-06 Microsoft Corporation Systems, methods, and interfaces for providing personalized search and information access
US20060074871A1 (en) 2004-09-30 2006-04-06 Microsoft Corporation System and method for incorporating anchor text into ranking search results
US20060074903A1 (en) 2004-09-30 2006-04-06 Microsoft Corporation System and method for ranking search results using click distance
RU2273879C2 (en) 2002-05-28 2006-04-10 Владимир Владимирович Насыпный Method for synthesis of self-teaching system for extracting knowledge from text documents for search engines
US7028029B2 (en) 2003-03-28 2006-04-11 Google Inc. Adaptive computation of ranking
US20060095416A1 (en) 2004-10-28 2006-05-04 Yahoo! Inc. Link-based spam detection
US7051023B2 (en) 2003-04-04 2006-05-23 Yahoo! Inc. Systems and methods for generating concept units from search queries
US20060136411A1 (en) * 2004-12-21 2006-06-22 Microsoft Corporation Ranking search results using feature extraction
US7072888B1 (en) 1999-06-16 2006-07-04 Triogo, Inc. Process for improving search engine efficiency using feedback
US20060149723A1 (en) 2002-05-24 2006-07-06 Microsoft Corporation System and method for providing search results with configurable scoring formula
US7076483B2 (en) 2001-08-27 2006-07-11 Xyleme Sa Ranking nodes in a graph
US7080073B1 (en) 2000-08-18 2006-07-18 Firstrain, Inc. Method and apparatus for focused crawling
US20060161534A1 (en) 2005-01-18 2006-07-20 Yahoo! Inc. Matching and ranking of sponsored search listings incorporating web search technology and web content
US7085755B2 (en) 2002-11-07 2006-08-01 Thomson Global Resources Ag Electronic document repository management and access system
US20060173828A1 (en) 2005-02-01 2006-08-03 Outland Research, Llc Methods and apparatus for using personal background data to improve the organization of documents retrieved in response to a search query
US20060173560A1 (en) 2004-10-07 2006-08-03 Bernard Widrow System and method for cognitive memory and auto-associative neural network based pattern recognition
US20060195440A1 (en) 2005-02-25 2006-08-31 Microsoft Corporation Ranking results using multiple nested ranking
US20060200460A1 (en) 2005-03-03 2006-09-07 Microsoft Corporation System and method for ranking search results using file types
US7107218B1 (en) 1999-10-29 2006-09-12 British Telecommunications Public Limited Company Method and apparatus for processing queries
US20060206460A1 (en) 2005-03-14 2006-09-14 Sanjay Gadkari Biasing search results
US20060206476A1 (en) 2005-03-10 2006-09-14 Yahoo!, Inc. Reranking and increasing the relevance of the results of Internet searches
US20060212423A1 (en) * 2005-03-16 2006-09-21 Rosie Jones System and method for biasing search results based on topic familiarity
US20060224554A1 (en) 2005-03-29 2006-10-05 Bailey David R Query revision using known highly-ranked queries
US20060248074A1 (en) 2005-04-28 2006-11-02 International Business Machines Corporation Term-statistics modification for category-based search
US7133870B1 (en) 1999-10-14 2006-11-07 Al Acquisitions, Inc. Index cards on network hosts for searching, rating, and ranking
KR20060116042A (en) 2005-05-09 2006-11-14 엔에이치엔(주) Personalized search method using cookie information and system for enabling the method
WO2006121269A1 (en) 2005-05-06 2006-11-16 Nhn Corporation Personalized search method and system for enabling the method
US20060259481A1 (en) 2005-05-12 2006-11-16 Xerox Corporation Method of analyzing documents
US20060282455A1 (en) 2005-06-13 2006-12-14 It Interactive Services Inc. System and method for ranking web content
US20060282306A1 (en) 2005-06-10 2006-12-14 Unicru, Inc. Employee selection via adaptive assessment
US7152059B2 (en) 2002-08-30 2006-12-19 Emergency24, Inc. System and method for predicting additional search results of a computerized database search user based on an initial search query
US20060287993A1 (en) 2005-06-21 2006-12-21 Microsoft Corporation High scale adaptive search systems and methods
US20060294100A1 (en) 2005-03-03 2006-12-28 Microsoft Corporation Ranking search results using language types
US20070038622A1 (en) 2005-08-15 2007-02-15 Microsoft Corporation Method ranking search results using biased click distance
US20070038616A1 (en) 2005-08-10 2007-02-15 Guha Ramanathan V Programmable search engine
US7181438B1 (en) 1999-07-21 2007-02-20 Alberti Anemometer, Llc Database access system
US20070050338A1 (en) 2005-08-29 2007-03-01 Strohm Alan C Mobile sitemaps
US20070067284A1 (en) 2005-09-21 2007-03-22 Microsoft Corporation Ranking functions using document usage statistics
US7197497B2 (en) 2003-04-25 2007-03-27 Overture Services, Inc. Method and apparatus for machine learning a document relevance function
US20070073748A1 (en) 2005-09-27 2007-03-29 Barney Jonathan A Method and system for probabilistically quantifying and visualizing relevance between two or more citationally or contextually related data objects
US20070085716A1 (en) 2005-09-30 2007-04-19 International Business Machines Corporation System and method for detecting matches of small edit distance
US20070094285A1 (en) 2005-10-21 2007-04-26 Microsoft Corporation Question answering over structured content on the web
US20070106659A1 (en) 2005-03-18 2007-05-10 Yunshan Lu Search engine that applies feedback from users to improve search results
US7228301B2 (en) 2003-06-27 2007-06-05 Microsoft Corporation Method for normalizing document metadata to improve search results using an alias relationship directory service
US7231399B1 (en) 2003-11-14 2007-06-12 Google Inc. Ranking documents based on large data sets
US20070150473A1 (en) 2005-12-22 2007-06-28 Microsoft Corporation Search By Document Type And Relevance
US7243102B1 (en) 2004-07-01 2007-07-10 Microsoft Corporation Machine directed improvement of ranking algorithms
US7246128B2 (en) 2002-06-12 2007-07-17 Jordahl Jena J Data storage, retrieval, manipulation and display tools enabling multiple hierarchical points of view
WO2007089289A2 (en) 2006-01-31 2007-08-09 Louis Wang Method for ranking and sorting electronic documents in a search result list based on relevance
US7260573B1 (en) 2004-05-17 2007-08-21 Google Inc. Personalizing anchor text scores in a search engine
US20070198459A1 (en) 2006-02-14 2007-08-23 Boone Gary N System and method for online information analysis
EP1462950B1 (en) 2003-03-27 2007-08-29 Sony Deutschland GmbH Method for language modelling
US7278105B1 (en) 2000-08-21 2007-10-02 Vignette Corporation Visualization and analysis of user clickpaths
US7283997B1 (en) 2003-05-14 2007-10-16 Apple Inc. System and method for ranking the relevance of documents retrieved by a query
WO2007123416A1 (en) 2006-04-24 2007-11-01 Telenor Asa Method and device for efficiently ranking documents in a similarity graph
US20070260597A1 (en) 2006-05-02 2007-11-08 Mark Cramer Dynamic search engine results employing user behavior
US20070276829A1 (en) 2004-03-31 2007-11-29 Niniane Wang Systems and methods for ranking implicit search results
EP1862916A1 (en) 2006-06-01 2007-12-05 Microsoft Corporation Indexing Documents for Information Retrieval based on additional feedback fields
US7308643B1 (en) 2003-07-03 2007-12-11 Google Inc. Anchor tag indexing in a web crawler system
WO2007149623A2 (en) 2006-04-25 2007-12-27 Infovell, Inc. Full text query and search systems and method of use
US20080005068A1 (en) 2006-06-28 2008-01-03 Microsoft Corporation Context-based search, retrieval, and awareness
US20080016053A1 (en) 2006-07-14 2008-01-17 Bea Systems, Inc. Administration Console to Select Rank Factors
JP2008033931A (en) 2006-07-26 2008-02-14 Xerox Corp Method for enrichment of text, method for acquiring text in response to query, and system
KR20080017685A (en) 2006-08-22 2008-02-27 에스케이커뮤니케이션즈 주식회사 Document ranking granting method and computer readable record medium thereof
US7346604B1 (en) 1999-10-15 2008-03-18 Hewlett-Packard Development Company, L.P. Method for ranking hypertext search results by analysis of hyperlinks from expert documents and keyword scope
KR20080024584A (en) 2006-09-14 2008-03-19 엔에이치엔(주) Method for making document score using book search and system for executing the method
US7386527B2 (en) 2002-12-06 2008-06-10 Kofax, Inc. Effective multi-class support vector machine classification
US20080140641A1 (en) 2006-12-07 2008-06-12 Yahoo! Inc. Knowledge and interests based search term ranking for search results validation
JP2008146424A (en) 2006-12-12 2008-06-26 Nippon Telegr & Teleph Corp <Ntt> Xml document conformity calculation method, its program, and information processor
US20080154888A1 (en) 2006-12-11 2008-06-26 Florian Michel Buron Viewport-Relative Scoring For Location Search Queries
US20080195596A1 (en) 2007-02-09 2008-08-14 Jacob Sisk System and method for associative matching
US7428530B2 (en) 2004-07-01 2008-09-23 Microsoft Corporation Dispersing search engine results by using page category information
US20090006358A1 (en) 2007-06-27 2009-01-01 Microsoft Corporation Search results
US20090006356A1 (en) 2007-06-27 2009-01-01 Oracle International Corporation Changing ranking algorithms based on customer settings
US20090024606A1 (en) 2007-07-20 2009-01-22 Google Inc. Identifying and Linking Similar Passages in a Digital Text Corpus
CN101360074A (en) 2008-09-27 2009-02-04 腾讯科技(深圳)有限公司 Method and system determining suspicious spam range
US20090070306A1 (en) 2007-09-07 2009-03-12 Mihai Stroe Systems and Methods for Processing Inoperative Document Links
US7519529B1 (en) 2001-06-29 2009-04-14 Microsoft Corporation System and methods for inferring informational goals and preferred level of detail of results in response to questions posed to an automated information-retrieval or question-answering service
US20090106235A1 (en) 2007-10-18 2009-04-23 Microsoft Corporation Document Length as a Static Relevance Feature for Ranking Search Results
WO2009072174A1 (en) 2007-12-03 2009-06-11 Pioneer Corporation Information retrieval apparatus, method for information retrieval, and retrieval processing program
US20090157607A1 (en) 2007-12-12 2009-06-18 Yahoo! Inc. Unsupervised detection of web pages corresponding to a similarity class
US20090164929A1 (en) 2007-12-20 2009-06-25 Microsoft Corporation Customizing Search Results
JP2009146248A (en) 2007-12-17 2009-07-02 Fujifilm Corp Content presenting system and program
US7562068B2 (en) 2004-06-30 2009-07-14 Microsoft Corporation System and method for ranking search results based on tracked user preferences
US7580568B1 (en) 2004-03-31 2009-08-25 Google Inc. Methods and systems for identifying an image as a representative image for an article
JP2009204442A (en) 2008-02-28 2009-09-10 Athlete Fa Kk Weighing device for particulate matter
US20090240680A1 (en) * 2008-03-20 2009-09-24 Microsoft Corporation Techniques to perform relative ranking for search results
US20090259651A1 (en) 2008-04-11 2009-10-15 Microsoft Corporation Search results ranking using editing distance and document information
US7606793B2 (en) 2004-09-27 2009-10-20 Microsoft Corporation System and method for scoping searches using index keys
JP2009252179A (en) 2008-04-10 2009-10-29 Ntt Docomo Inc Recommendation information evaluation device and recommendation information evaluation method
US20090276421A1 (en) 2008-05-04 2009-11-05 Gang Qiu Method and System for Re-ranking Search Results
US20090307209A1 (en) 2008-06-10 2009-12-10 David Carmel Term-statistics modification for category-based search
US7644107B2 (en) 2004-09-30 2010-01-05 Microsoft Corporation System and method for batched indexing of network documents
US7689559B2 (en) 2006-02-08 2010-03-30 Telenor Asa Document similarity scoring and ranking method, device and computer program product
US7689531B1 (en) 2005-09-28 2010-03-30 Trend Micro Incorporated Automatic charset detection using support vector machines with charset grouping
US7693829B1 (en) 2005-04-25 2010-04-06 Google Inc. Search engine with fill-the-blanks capability
US7716225B1 (en) 2004-06-17 2010-05-11 Google Inc. Ranking documents based on user behavior and/or feature data
US7720830B2 (en) * 2006-07-31 2010-05-18 Microsoft Corporation Hierarchical conditional random fields for web extraction
US7836391B2 (en) 2003-06-10 2010-11-16 Google Inc. Document search engine including highlighting of confident results
US7836048B2 (en) 2007-11-19 2010-11-16 Red Hat, Inc. Socially-derived relevance in search engine results
US7840569B2 (en) 2007-10-18 2010-11-23 Microsoft Corporation Enterprise relevancy ranking using a neural network
US7844589B2 (en) 2003-11-18 2010-11-30 Yahoo! Inc. Method and apparatus for performing a search
US20110106850A1 (en) 2009-10-29 2011-05-05 Microsoft Corporation Relevant Individual Searching Using Managed Property and Ranking Features
US20110137893A1 (en) 2009-12-04 2011-06-09 Microsoft Corporation Custom ranking model schema
US7962462B1 (en) 2005-05-31 2011-06-14 Google Inc. Deriving and using document and site quality signals from search query streams
EP0950961B1 (en) 1998-04-17 2011-06-22 Xerox Corporation Methods for interactive visualization of spreading activation using time tubes and disk trees
US20110235909A1 (en) 2010-03-26 2011-09-29 International Business Machines Corporation Analyzing documents using stored templates
US20110295850A1 (en) 2010-06-01 2011-12-01 Microsoft Corporation Detection of junk in search result ranking
US8165406B2 (en) 2007-12-12 2012-04-24 Microsoft Corp. Interactive concept learning in image search
US8326829B2 (en) 2008-10-17 2012-12-04 Centurylink Intellectual Property Llc System and method for displaying publication dates for search results
US8370331B2 (en) 2010-07-02 2013-02-05 Business Objects Software Limited Dynamic visualization of search results on a graphical user interface
US8412702B2 (en) 2008-03-12 2013-04-02 Yahoo! Inc. System, method, and/or apparatus for reordering search results
US20130198174A1 (en) 2012-01-27 2013-08-01 Microsoft Corporation Re-ranking search results
US8909655B1 (en) 2007-10-11 2014-12-09 Google Inc. Time based ranking

Patent Citations (431)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2009509275T5 (en) 2009-10-08
US6182113B2 (en)
US6182067B2 (en)
US6182065B2 (en)
JPS62297950A (en) 1986-06-13 1987-12-25 Ibm Journaling of data system
US5634124A (en) 1987-08-21 1997-05-27 Wang Laboratories, Inc. Data integration by object management
US5369778A (en) 1987-08-21 1994-11-29 Wang Laboratories, Inc. Data processor that customizes program behavior by using a resource retrieval capability
US5222236A (en) 1988-04-29 1993-06-22 Overdrive Systems, Inc. Multiple integrated document assembly data processing system
US5321833A (en) 1990-08-29 1994-06-14 Gte Laboratories Incorporated Adaptive ranking system for information retrieval
US5257577A (en) 1991-04-01 1993-11-02 Clark Melvin D Apparatus for assist in recycling of refuse
US5544360A (en) 1992-11-23 1996-08-06 Paragon Concepts, Inc. Method for accessing computer files and data, using linked categories assigned to each data file record on entry of the data file record
US6202058B1 (en) 1994-04-25 2001-03-13 Apple Computer, Inc. System for ranking the relevance of information objects accessed by computer users
US5606609A (en) 1994-09-19 1997-02-25 Scientific-Atlanta Electronic document verification system and method
US5594660A (en) 1994-09-30 1997-01-14 Cirrus Logic, Inc. Programmable audio-video synchronization method and apparatus for multimedia systems
US5893092A (en) 1994-12-06 1999-04-06 University Of Central Florida Relevancy ranking using statistical ranking, semantics, relevancy feedback and small pieces of text
US5729730A (en) 1995-03-28 1998-03-17 Dex Information Systems, Inc. Method and apparatus for improved information storage and retrieval system
US5826269A (en) 1995-06-21 1998-10-20 Microsoft Corporation Electronic mail interface for a network server
US5933851A (en) 1995-09-29 1999-08-03 Sony Corporation Time-stamp and hash-based file modification monitor with multi-user notification and method thereof
US6032196A (en) 1995-12-13 2000-02-29 Digital Equipment Corporation System for adding a new entry to a web page table upon receiving a web page including a link to another web page not having a corresponding entry in the web page table
US6269370B1 (en) 1996-02-21 2001-07-31 Infoseek Corporation Web scan process
US6775664B2 (en) 1996-04-04 2004-08-10 Lycos, Inc. Information filter system and method for integrated content-based and collaborative/adaptive feedback queries
US6041323A (en) * 1996-04-17 2000-03-21 International Business Machines Corporation Information search method, information search device, and storage medium for storing an information search program
US5905866A (en) 1996-04-30 1999-05-18 A.I. Soft Corporation Data-update monitoring in communications network
US5828999A (en) * 1996-05-06 1998-10-27 Apple Computer, Inc. Method and system for deriving a large-span semantic language model for large-vocabulary recognition systems
US6038610A (en) 1996-07-17 2000-03-14 Microsoft Corporation Storage of sitemaps at server sites for holding information regarding content
US6178419B1 (en) 1996-07-31 2001-01-23 British Telecommunications Plc Data access system
US6317741B1 (en) 1996-08-09 2001-11-13 Altavista Company Technique for ranking records of a database
US5765150A (en) 1996-08-09 1998-06-09 Digital Equipment Corporation Method for statistically projecting the ranking of information
US6070158A (en) 1996-08-14 2000-05-30 Infoseek Corporation Real-time document collection search engine with phrase indexing
JPH1091638A (en) 1996-09-17 1998-04-10 Toshiba Corp Search system
US5870739A (en) 1996-09-20 1999-02-09 Novell, Inc. Hybrid query apparatus and method
US5893116A (en) 1996-09-30 1999-04-06 Novell, Inc. Accessing network resources using network resource replicator and captured login script for use when the computer is disconnected from the network
US5870740A (en) 1996-09-30 1999-02-09 Apple Computer, Inc. System and method for improving the ranking of information retrieval results for short queries
US6222559B1 (en) 1996-10-02 2001-04-24 Nippon Telegraph And Telephone Corporation Method and apparatus for display of hierarchical structures
US6182065B1 (en) 1996-11-06 2001-01-30 International Business Machines Corp. Method and system for weighting the search results of a database search engine
US6326962B1 (en) 1996-12-23 2001-12-04 Doubleagent Llc Graphic user interface for database system
US6285999B1 (en) * 1997-01-10 2001-09-04 The Board Of Trustees Of The Leland Stanford Junior University Method for node ranking in a linked database
US5920859A (en) 1997-02-05 1999-07-06 Idd Enterprises, L.P. Hypertext document retrieval system and method
US6415319B1 (en) 1997-02-07 2002-07-02 Sun Microsystems, Inc. Intelligent network browser using incremental conceptual indexer
US5960383A (en) 1997-02-25 1999-09-28 Digital Equipment Corporation Extraction of key sections from texts using automatic indexing techniques
JPH10240757A (en) 1997-02-27 1998-09-11 Hitachi Ltd Cooperative decentralized retrieval system
US5890147A (en) 1997-03-07 1999-03-30 Microsoft Corporation Scope testing of documents in a search engine using document to folder mapping
US5848404A (en) 1997-03-24 1998-12-08 International Business Machines Corporation Fast query search in large dimension database
US6272507B1 (en) 1997-04-09 2001-08-07 Xerox Corporation System for ranking search results from a collection of documents using spreading activation techniques
US6484204B1 (en) 1997-05-06 2002-11-19 At&T Corp. System and method for allocating requests for objects and managing replicas of objects on a network
US6182067B1 (en) 1997-06-02 2001-01-30 Knowledge Horizons Pty Ltd. Methods and systems for knowledge management
US6029164A (en) 1997-06-16 2000-02-22 Digital Equipment Corporation Method and apparatus for organizing and accessing electronic mail messages using labels and full text and label indexing
US6012053A (en) 1997-06-23 2000-01-04 Lycos, Inc. Computer system with user-controlled relevance ranking of search results
US6247013B1 (en) 1997-06-30 2001-06-12 Canon Kabushiki Kaisha Hyper text reading system
US20010042076A1 (en) 1997-06-30 2001-11-15 Ryoji Fukuda A hypertext reader which performs a reading process on a hierarchically constructed hypertext
US5933822A (en) 1997-07-22 1999-08-03 Microsoft Corporation Apparatus and methods for an information retrieval system that employs natural language processing of search results to improve overall precision
US5983216A (en) 1997-09-12 1999-11-09 Infoseek Corporation Performing automated document collection and selection by providing a meta-index with meta-index values indentifying corresponding document collections
US6182113B1 (en) 1997-09-16 2001-01-30 International Business Machines Corporation Dynamic multiplexing of hyperlinks and bookmarks
US5956722A (en) 1997-09-23 1999-09-21 At&T Corp. Method for effective indexing of partially dynamic documents
US6999959B1 (en) 1997-10-10 2006-02-14 Nec Laboratories America, Inc. Meta search engine
US6026398A (en) 1997-10-16 2000-02-15 Imarket, Incorporated System and methods for searching and matching databases
US6070191A (en) 1997-10-17 2000-05-30 Lucent Technologies Inc. Data distribution techniques for load-balanced fault-tolerant web access
US6351467B1 (en) 1997-10-27 2002-02-26 Hughes Electronics Corporation System and method for multicasting multimedia content
US6594682B2 (en) 1997-10-28 2003-07-15 Microsoft Corporation Client-side system for scheduling delivery of web content and locally managing the web content
US6128701A (en) 1997-10-28 2000-10-03 Cache Flow, Inc. Adaptive and predictive cache refresh policy
US6553364B1 (en) 1997-11-03 2003-04-22 Yahoo! Inc. Information retrieval from hierarchical compound documents
US5943670A (en) 1997-11-21 1999-08-24 International Business Machines Corporation System and method for categorizing objects in combined categories
US5987457A (en) 1997-11-25 1999-11-16 Acceleration Software International Corporation Query refinement method for searching documents
US6473752B1 (en) 1997-12-04 2002-10-29 Micron Technology, Inc. Method and system for locating documents based on previously accessed documents
US6389436B1 (en) 1997-12-15 2002-05-14 International Business Machines Corporation Enhanced hypertext categorization using hyperlinks
US6145003A (en) 1997-12-17 2000-11-07 Microsoft Corporation Method of web crawling utilizing address mapping
US7010532B1 (en) 1997-12-31 2006-03-07 International Business Machines Corporation Low overhead methods and apparatus for shared access storage devices
US6151624A (en) 1998-02-03 2000-11-21 Realnames Corporation Navigating network resources based on metadata
JPH11232300A (en) 1998-02-18 1999-08-27 Nri & Ncc Co Ltd Browsing client server system
US6349308B1 (en) 1998-02-25 2002-02-19 Korea Advanced Institute Of Science & Technology Inverted index storage structure using subindexes and large objects for tight coupling of information retrieval with database management systems
US6185558B1 (en) 1998-03-03 2001-02-06 Amazon.Com, Inc. Identifying the items most relevant to a current query based on items selected in connection with similar queries
US5913210A (en) 1998-03-27 1999-06-15 Call; Charles G. Methods and apparatus for disseminating product information via the internet
US6125361A (en) 1998-04-10 2000-09-26 International Business Machines Corporation Feature diffusion across hyperlinks
EP0950961B1 (en) 1998-04-17 2011-06-22 Xerox Corporation Methods for interactive visualization of spreading activation using time tubes and disk trees
US6167402A (en) 1998-04-27 2000-12-26 Sun Microsystems, Inc. High performance message store
US6314421B1 (en) 1998-05-12 2001-11-06 David M. Sharnoff Method and apparatus for indexing documents for message filtering
JPH11328191A (en) 1998-05-13 1999-11-30 Nec Corp Www robot retrieving system
US6098064A (en) 1998-05-22 2000-08-01 Xerox Corporation Prefetching and caching documents according to probability ranked need S list
US6285367B1 (en) 1998-05-26 2001-09-04 International Business Machines Corporation Method and apparatus for displaying and navigating a graph
US6182085B1 (en) 1998-05-28 2001-01-30 International Business Machines Corporation Collaborative team crawling:Large scale information gathering over the internet
US6208988B1 (en) 1998-06-01 2001-03-27 Bigchalk.Com, Inc. Method for identifying themes associated with a search query using metadata and for organizing documents responsive to the search query in accordance with the themes
US6240408B1 (en) 1998-06-08 2001-05-29 Kcsl, Inc. Method and system for retrieving relevant documents from a database
US6006225A (en) 1998-06-15 1999-12-21 Amazon.Com Refining search queries by the suggestion of correlated terms from prior searches
US7003442B1 (en) 1998-06-24 2006-02-21 Fujitsu Limited Document file group organizing apparatus and method thereof
US6216123B1 (en) 1998-06-24 2001-04-10 Novell, Inc. Method and system for rapid retrieval in a full text indexing system
US6638314B1 (en) 1998-06-26 2003-10-28 Microsoft Corporation Method of web crawling utilizing crawl numbers
US6424966B1 (en) 1998-06-30 2002-07-23 Microsoft Corporation Synchronizing crawler with notification source
US6199081B1 (en) 1998-06-30 2001-03-06 Microsoft Corporation Automatic tagging of documents and exclusion by content
US6775659B2 (en) 1998-08-26 2004-08-10 Symtec Limited Methods and devices for mapping data files
US6324551B1 (en) 1998-08-31 2001-11-27 Xerox Corporation Self-contained document management based on document properties
RU2138076C1 (en) 1998-09-14 1999-09-20 Закрытое акционерное общество "МедиаЛингва" Data retrieval system in computer network
US6115709A (en) 1998-09-18 2000-09-05 Tacit Knowledge Systems, Inc. Method and system for constructing a knowledge profile of a user having unrestricted and restricted access portions according to respective levels of confidence of content of the portions
US6549897B1 (en) 1998-10-09 2003-04-15 Microsoft Corporation Method and system for calculating phrase-document importance
US6385602B1 (en) 1998-11-03 2002-05-07 E-Centives, Inc. Presentation of search results using dynamic categorization
US6360215B1 (en) 1998-11-03 2002-03-19 Inktomi Corporation Method and apparatus for retrieving documents based on information other than document content
US6701318B2 (en) 1998-11-18 2004-03-02 Harris Corporation Multiple engine information retrieval and visualization system
US6628304B2 (en) 1998-12-09 2003-09-30 Cisco Technology, Inc. Method and apparatus providing a graphical user interface for representing and navigating hierarchical networks
US6167369A (en) 1998-12-23 2000-12-26 Xerox Company Automatic language identification using both N-gram and word information
JP2000194713A (en) 1998-12-25 2000-07-14 Nippon Telegr & Teleph Corp <Ntt> Method and device for retrieving character string, and storage medium stored with character string retrieval program
US20030074368A1 (en) 1999-01-26 2003-04-17 Hinrich Schuetze System and method for quantitatively representing data objects in vector space
US6418433B1 (en) 1999-01-28 2002-07-09 International Business Machines Corporation System and method for focussed web crawling
US6654742B1 (en) 1999-02-12 2003-11-25 International Business Machines Corporation Method and system for document collection final search result by arithmetical operations between search results sorted by multiple ranking metrics
US20030217047A1 (en) 1999-03-23 2003-11-20 Insightful Corporation Inverse inference engine for high performance web search
US6862710B1 (en) 1999-03-23 2005-03-01 Insightful Corporation Internet navigation using soft hyperlinks
US20040215664A1 (en) 1999-03-31 2004-10-28 Microsoft Corporation Method for promoting contextual information to display pages containing hyperlinks
US6304864B1 (en) 1999-04-20 2001-10-16 Textwise Llc System for retrieving multimedia information from the internet using multiple evolving intelligent agents
US6336117B1 (en) 1999-04-30 2002-01-01 International Business Machines Corporation Content-indexing search system and method providing search results consistent with content filtering and blocking policies implemented in a blocking engine
EP1050830A3 (en) 1999-05-05 2002-04-17 Xerox Corporation System and method for collaborative ranking of search results employing user and group profiles
US6327590B1 (en) 1999-05-05 2001-12-04 Xerox Corporation System and method for collaborative ranking of search results employing user and group profiles derived from document collection content analysis
US6990628B1 (en) 1999-06-14 2006-01-24 Yahoo! Inc. Method and apparatus for measuring similarity among electronic documents
US7072888B1 (en) 1999-06-16 2006-07-04 Triogo, Inc. Process for improving search engine efficiency using feedback
US6973490B1 (en) 1999-06-23 2005-12-06 Savvis Communications Corp. Method and system for object-level web performance and analysis
US6547829B1 (en) 1999-06-30 2003-04-15 Microsoft Corporation Method and system for detecting duplicate documents in web crawls
US6631369B1 (en) 1999-06-30 2003-10-07 Microsoft Corporation Method and system for incremental web crawling
US6873982B1 (en) 1999-07-16 2005-03-29 International Business Machines Corporation Ordering of database search results based on user feedback
US6557036B1 (en) 1999-07-20 2003-04-29 Sun Microsystems, Inc. Methods and apparatus for site wide monitoring of electronic mail systems
US7181438B1 (en) 1999-07-21 2007-02-20 Alberti Anemometer, Llc Database access system
US6598047B1 (en) 1999-07-26 2003-07-22 David W. Russell Method and system for searching text
CA2279119C (en) 1999-07-29 2004-10-19 Ibm Canada Limited-Ibm Canada Limitee Heuristic-based conditional data indexing
JP2001052017A (en) 1999-08-11 2001-02-23 Fuji Xerox Co Ltd Hypertext analyzer
US6442606B1 (en) 1999-08-12 2002-08-27 Inktomi Corporation Method and apparatus for identifying spoof documents
US6636853B1 (en) 1999-08-30 2003-10-21 Morphism, Llc Method and apparatus for representing and navigating search results
US6381597B1 (en) 1999-10-07 2002-04-30 U-Know Software Corporation Electronic shopping agent which is capable of operating with vendor sites which have disparate formats
US7133870B1 (en) 1999-10-14 2006-11-07 Al Acquisitions, Inc. Index cards on network hosts for searching, rating, and ranking
US7346604B1 (en) 1999-10-15 2008-03-18 Hewlett-Packard Development Company, L.P. Method for ranking hypertext search results by analysis of hyperlinks from expert documents and keyword scope
US20030004952A1 (en) 1999-10-18 2003-01-02 Mark Nixon Accessing and updating a configuration database from distributed physical locations within a process control system
JP2001117934A (en) 1999-10-19 2001-04-27 Hitachi Ltd Method and system for managing electronic document and recording medium
US7107218B1 (en) 1999-10-29 2006-09-12 British Telecommunications Public Limited Company Method and apparatus for processing queries
US6263364B1 (en) 1999-11-02 2001-07-17 Alta Vista Company Web crawler system using plurality of parallel priority level queues having distinct associated download priority levels for prioritizing document downloading and maintaining document freshness
US6351755B1 (en) 1999-11-02 2002-02-26 Alta Vista Company System and method for associating an extensible set of data with documents downloaded by a web crawler
US6418453B1 (en) 1999-11-03 2002-07-09 International Business Machines Corporation Network repository service for efficient web crawling
US6418452B1 (en) 1999-11-03 2002-07-09 International Business Machines Corporation Network repository service directory for efficient web crawling
US6539376B1 (en) 1999-11-15 2003-03-25 International Business Machines Corporation System and method for the automatic mining of new relationships
US7016540B1 (en) 1999-11-24 2006-03-21 Nec Corporation Method and system for segmentation, classification, and summarization of video images
US6886129B1 (en) 1999-11-24 2005-04-26 International Business Machines Corporation Method and system for trawling the World-wide Web to identify implicitly-defined communities of web pages
US6772141B1 (en) 1999-12-14 2004-08-03 Novell, Inc. Method and apparatus for organizing and using indexes utilizing a search decision table
US6718324B2 (en) 2000-01-14 2004-04-06 International Business Machines Corporation Metadata search results ranking system
US6546388B1 (en) 2000-01-14 2003-04-08 International Business Machines Corporation Metadata search results ranking system
EP1120717B1 (en) 2000-01-28 2009-12-02 Microsoft Corporation Adaptive web crawling using a statistical model
US20050086583A1 (en) 2000-01-28 2005-04-21 Microsoft Corporation Proxy server using a statistical model
US7328401B2 (en) 2000-01-28 2008-02-05 Microsoft Corporation Adaptive web crawling using a statistical model
US6883135B1 (en) 2000-01-28 2005-04-19 Microsoft Corporation Proxy server using a statistical model
US20040199497A1 (en) 2000-02-08 2004-10-07 Sybase, Inc. System and Methodology for Extraction and Aggregation of Data from Dynamic Content
US6931397B1 (en) 2000-02-11 2005-08-16 International Business Machines Corporation System and method for automatic generation of dynamic search abstracts contain metadata by crawler
US6910029B1 (en) 2000-02-22 2005-06-21 International Business Machines Corporation System for weighted indexing of hierarchical documents
JP2001265774A (en) 2000-03-16 2001-09-28 Nippon Telegr & Teleph Corp <Ntt> Method and device for retrieving information, recording medium with recorded information retrieval program and hypertext information retrieving system
US6516312B1 (en) 2000-04-04 2003-02-04 International Business Machine Corporation System and method for dynamically associating keywords with domain-specific search engine queries
US6633867B1 (en) 2000-04-05 2003-10-14 International Business Machines Corporation System and method for providing a session query within the context of a dynamic search result set
US6549896B1 (en) 2000-04-07 2003-04-15 Nec Usa, Inc. System and method employing random walks for mining web page associations and usage to optimize user-oriented web page refresh and pre-fetch scheduling
US6718365B1 (en) 2000-04-13 2004-04-06 International Business Machines Corporation Method, system, and program for ordering search results using an importance weighting
US6859800B1 (en) 2000-04-26 2005-02-22 Global Information Research And Technologies Llc System for fulfilling an information need
US20050044071A1 (en) 2000-06-08 2005-02-24 Ingenuity Systems, Inc. Techniques for facilitating information acquisition and storage
DE10029644A1 (en) 2000-06-16 2002-01-17 Deutsche Telekom Ag Hypertext documents evaluation method using search engine, involves calculating real relevance value for each document based on precalculated relevance value and cross references of document
US20020016787A1 (en) * 2000-06-28 2002-02-07 Matsushita Electric Industrial Co., Ltd. Apparatus for retrieving similar documents and apparatus for extracting relevant keywords
US6671683B2 (en) 2000-06-28 2003-12-30 Matsushita Electric Industrial Co., Ltd. Apparatus for retrieving similar documents and apparatus for extracting relevant keywords
US6678692B1 (en) 2000-07-10 2004-01-13 Northrop Grumman Corporation Hierarchy statistical analysis system and method
JP2002024015A (en) 2000-07-11 2002-01-25 Misawa Van Corp Method for constructing client server system
US6601075B1 (en) 2000-07-27 2003-07-29 International Business Machines Corporation System and method of ranking and retrieving documents based on authority scores of schemas and documents
US6633868B1 (en) 2000-07-28 2003-10-14 Shermann Loyall Min System and method for context-based document retrieval
US6598040B1 (en) 2000-08-14 2003-07-22 International Business Machines Corporation Method and system for processing electronic search expressions
US7080073B1 (en) 2000-08-18 2006-07-18 Firstrain, Inc. Method and apparatus for focused crawling
US7278105B1 (en) 2000-08-21 2007-10-02 Vignette Corporation Visualization and analysis of user clickpaths
KR20020015838A (en) 2000-08-23 2002-03-02 전홍건 Method for re-adjusting ranking of document to use user's profile and entropy
US6959326B1 (en) 2000-08-24 2005-10-25 International Business Machines Corporation Method, system, and program for gathering indexable metadata on content at a data repository
US20030217052A1 (en) 2000-08-24 2003-11-20 Celebros Ltd. Search engine method and apparatus
US20020026390A1 (en) 2000-08-25 2002-02-28 Jonas Ulenas Method and apparatus for obtaining consumer product preferences through product selection and evaluation
JP2002091843A (en) 2000-09-11 2002-03-29 Nippon Telegr & Teleph Corp <Ntt> Device and method for selecting server and recording medium recording server selection program
US20020032772A1 (en) 2000-09-14 2002-03-14 Bjorn Olstad Method for searching and analysing information in data networks
US6598051B1 (en) 2000-09-19 2003-07-22 Altavista Company Web page connectivity server
US6871202B2 (en) 2000-10-25 2005-03-22 Overture Services, Inc. Method and apparatus for ranking web page search results
JP2002132769A (en) 2000-10-25 2002-05-10 Nippon Telegr & Teleph Corp <Ntt> Method and device for multilateral retrieval service and recording medium recording program therefor
US6560600B1 (en) 2000-10-25 2003-05-06 Alta Vista Company Method and apparatus for ranking Web page search results
JP2002140365A (en) 2000-11-01 2002-05-17 Mitsubishi Electric Corp Data retrieving method
US20020055940A1 (en) 2000-11-07 2002-05-09 Charles Elkan Method and system for selecting documents by measuring document quality
US6622140B1 (en) 2000-11-15 2003-09-16 Justsystem Corporation Method and apparatus for analyzing affect and emotion in text
JP2002157271A (en) 2000-11-20 2002-05-31 Yozan Inc Browser device, server device, recording medium, retrieving system and retrieving method
US20020062323A1 (en) 2000-11-20 2002-05-23 Yozan Inc Browser apparatus, server apparatus, computer-readable medium, search system and search method
WO2002042862A3 (en) 2000-11-21 2002-09-19 Singingfish Com A system and process for mediated crawling
US20020099694A1 (en) 2000-11-21 2002-07-25 Diamond Theodore George Full-text relevancy ranking
US20050187965A1 (en) 2000-11-21 2005-08-25 Abajian Aram C. Grouping multimedia and streaming media search results
US20020107861A1 (en) 2000-12-07 2002-08-08 Kerry Clendinning System and method for collecting, associating, normalizing and presenting product and vendor information on a distributed network
US20050055347A9 (en) 2000-12-08 2005-03-10 Ingenuity Systems, Inc. Method and system for performing information extraction and quality control for a knowledgebase
US20020078045A1 (en) 2000-12-14 2002-06-20 Rabindranath Dutta System, method, and program for ranking search results using user category weighting
US7065523B2 (en) 2000-12-27 2006-06-20 Microsoft Corporation Scoping queries in a search engine
US20020083054A1 (en) 2000-12-27 2002-06-27 Kyle Peltonen Scoping queries in a search engine
US7415459B2 (en) 2000-12-27 2008-08-19 Microsoft Corporation Scoping queries in a search engine
US6898592B2 (en) 2000-12-27 2005-05-24 Microsoft Corporation Scoping queries in a search engine
JP2002202992A (en) 2000-12-28 2002-07-19 Speed System:Kk Homepage retrieval system
US6778997B2 (en) 2001-01-05 2004-08-17 International Business Machines Corporation XML: finding authoritative pages for mining communities based on page structure criteria
US20020169800A1 (en) 2001-01-05 2002-11-14 International Business Machines Corporation XML: finding authoritative pages for mining communities based on page structure criteria
US7356530B2 (en) 2001-01-10 2008-04-08 Looksmart, Ltd. Systems and methods of retrieving relevant information
US20020129014A1 (en) 2001-01-10 2002-09-12 Kim Brian S. Systems and methods of retrieving relevant information
US20030208482A1 (en) 2001-01-10 2003-11-06 Kim Brian S. Systems and methods of retrieving relevant information
US20020129015A1 (en) 2001-01-18 2002-09-12 Maureen Caudill Method and system of ranking and clustering for document indexing and retrieval
US7496561B2 (en) 2001-01-18 2009-02-24 Science Applications International Corporation Method and system of ranking and clustering for document indexing and retrieval
US20040111408A1 (en) 2001-01-18 2004-06-10 Science Applications International Corporation Method and system of ranking and clustering for document indexing and retrieval
US6766316B2 (en) 2001-01-18 2004-07-20 Science Applications International Corporation Method and system of ranking and clustering for document indexing and retrieval
US6725259B1 (en) 2001-01-30 2004-04-20 Google Inc. Ranking search results by reranking the results based on local inter-connectivity
US6526440B1 (en) 2001-01-30 2003-02-25 Google, Inc. Ranking search results by reranking the results based on local inter-connectivity
US20020103798A1 (en) 2001-02-01 2002-08-01 Abrol Mani S. Adaptive document ranking method based on user behavior
US20020107886A1 (en) 2001-02-07 2002-08-08 Gentner Donald R. Method and apparatus for automatic document electronic versioning system
US20040093328A1 (en) 2001-02-08 2004-05-13 Aditya Damle Methods and systems for automated semantic knowledge leveraging graph theoretic analysis and the inherent structure of communication
JP2002245089A (en) 2001-02-19 2002-08-30 Hitachi Eng Co Ltd Web page retrieval system, secondary information collecting device and interface unit
US20020165873A1 (en) * 2001-02-22 2002-11-07 International Business Machines Corporation Retrieving handwritten documents using multiple document recognizers and techniques allowing both typed and handwritten queries
US20020123988A1 (en) 2001-03-02 2002-09-05 Google, Inc. Methods and apparatus for employing usage statistics in document retrieval
US20020169595A1 (en) 2001-03-30 2002-11-14 Yevgeny Agichtein Method for retrieving answers from an information retrieval system
US20020169770A1 (en) 2001-04-27 2002-11-14 Kim Brian Seong-Gon Apparatus and method that categorize a collection of documents into a hierarchy of categories that are defined by the collection of documents
US20030037074A1 (en) 2001-05-01 2003-02-20 Ibm Corporation System and method for aggregating ranking results from various sources to improve the results of web searching
JP2002366549A (en) 2001-05-07 2002-12-20 Nec Corp Selective retrieval metasearch engine and method for performing selective retrieval
US20020169754A1 (en) 2001-05-08 2002-11-14 Jianchang Mao Apparatus and method for adaptively ranking search results
US6738764B2 (en) 2001-05-08 2004-05-18 Verity, Inc. Apparatus and method for adaptively ranking search results
US20030065706A1 (en) 2001-05-10 2003-04-03 Smyth Barry Joseph Intelligent internet website with hierarchical menu
US20020168106A1 (en) 2001-05-11 2002-11-14 Miroslav Trajkovic Palette-based histogram matching with recursive histogram vector generation
US20030088545A1 (en) 2001-06-18 2003-05-08 Pavitra Subramaniam System and method to implement a persistent and dismissible search center frame
US20030028520A1 (en) 2001-06-20 2003-02-06 Alpha Shamim A. Method and system for response time optimization of data query rankings and retrieval
US7519529B1 (en) 2001-06-29 2009-04-14 Microsoft Corporation System and methods for inferring informational goals and preferred level of detail of results in response to questions posed to an automated information-retrieval or question-answering service
US7039234B2 (en) 2001-07-19 2006-05-02 Microsoft Corporation Electronic ink as a software object
US20030053084A1 (en) 2001-07-19 2003-03-20 Geidl Erik M. Electronic ink as a software object
WO2003009180A3 (en) 2001-07-19 2003-11-06 Computer Ass Think Inc Method and system for reorganizing a tablespace in a database
EP1282060A2 (en) 2001-08-03 2003-02-05 Overture Services, Inc. System and method for providing place and price protection in a search result list generated by a computer network search engine
US20030061201A1 (en) 2001-08-13 2003-03-27 Xerox Corporation System for propagating enrichment between documents
US6868411B2 (en) 2001-08-13 2005-03-15 Xerox Corporation Fuzzy text categorizer
JP2003076715A (en) 2001-08-20 2003-03-14 Nhn Corp Method and system for retrieving web pages, program and recording medium
JP2003067419A (en) 2001-08-24 2003-03-07 Toshiba Corp Information retrieving method and information retrieval system
US7076483B2 (en) 2001-08-27 2006-07-11 Xyleme Sa Ranking nodes in a graph
US20030046389A1 (en) 2001-09-04 2003-03-06 Thieme Laura M. Method for monitoring a web site's keyword visibility in search engines and directories and resulting traffic from such keyword visibility
US20030055810A1 (en) 2001-09-18 2003-03-20 International Business Machines Corporation Front-end weight factor search criteria
US6766422B2 (en) 2001-09-27 2004-07-20 Siemens Information And Communication Networks, Inc. Method and system for web caching based on predictive usage
US6944609B2 (en) 2001-10-18 2005-09-13 Lycos, Inc. Search results using editor feedback
US20040205497A1 (en) 2001-10-22 2004-10-14 Chiang Alexander System for automatic generation of arbitrarily indexed hyperlinked text
RU2001128643A (en) 2001-10-24 2003-07-20 Закрытое акционерное общество "МедиаЛингва" A method of determining the rating and ranking of links users to bypass tract pages Web site hosted in a device node Internet processing
JP2003208434A (en) 2001-11-07 2003-07-25 Nec Corp Information retrieval system, and information retrieval method using the same
US20030101183A1 (en) 2001-11-26 2003-05-29 Navin Kabra Information retrieval index allowing updating while in use
US6763362B2 (en) 2001-11-30 2004-07-13 Micron Technology, Inc. Method and system for updating a search engine
US20030135490A1 (en) 2002-01-15 2003-07-17 Barrett Michael E. Enhanced popularity ranking
US20030217007A1 (en) 2002-01-29 2003-11-20 Sony Corporation Method for providing and obtaining content
US6829606B2 (en) 2002-02-14 2004-12-07 Infoglide Software Corporation Similarity search engine for use with relational databases
JP2003248696A (en) 2002-02-22 2003-09-05 Nippon Telegr & Teleph Corp <Ntt> Page rating/filtering method, device, and program, and computer readable recording medium recording the program
US20060004732A1 (en) 2002-02-26 2006-01-05 Odom Paul S Search engine methods and systems for generating relevant search results and advertisements
US6934714B2 (en) 2002-03-04 2005-08-23 Intelesis Engineering, Inc. Method and system for identification and maintenance of families of data records
US20030195882A1 (en) 2002-04-11 2003-10-16 Lee Chung Hee Homepage searching method using similarity recalculation based on URL substring relationship
KR20030080826A (en) 2002-04-11 2003-10-17 한국전자통신연구원 Effective homepage searching method using similarity recalculation based on url substring relationship
KR20030082109A (en) 2002-04-16 2003-10-22 (주)메타웨이브 Method and System for Providing Information and Retrieving Index Word using AND Operator
US20040003028A1 (en) 2002-05-08 2004-01-01 David Emmett Automatic display of web content to smaller display devices: improved summarization and navigation
US20060149723A1 (en) 2002-05-24 2006-07-06 Microsoft Corporation System and method for providing search results with configurable scoring formula
RU2273879C2 (en) 2002-05-28 2006-04-10 Владимир Владимирович Насыпный Method for synthesis of self-teaching system for extracting knowledge from text documents for search engines
US20040006559A1 (en) 2002-05-29 2004-01-08 Gange David M. System, apparatus, and method for user tunable and selectable searching of a database using a weigthted quantized feature vector
US7246128B2 (en) 2002-06-12 2007-07-17 Jordahl Jena J Data storage, retrieval, manipulation and display tools enabling multiple hierarchical points of view
JP2004021589A (en) 2002-06-17 2004-01-22 Nec System Technologies Ltd Internet information retrieval system
JP2004054588A (en) 2002-07-19 2004-02-19 Just Syst Corp Document retrieval device and method and program for making computer execute the same method
US20050055340A1 (en) 2002-07-26 2005-03-10 Brainbow, Inc. Neural-based internet search engine with fuzzy and learning processes implemented by backward propogation
US20040024752A1 (en) 2002-08-05 2004-02-05 Yahoo! Inc. Method and apparatus for search ranking using human input and automated ranking
US7152059B2 (en) 2002-08-30 2006-12-19 Emergency24, Inc. System and method for predicting additional search results of a computerized database search user based on an initial search query
US20040049766A1 (en) 2002-09-09 2004-03-11 Bloch Joshua J. Method and apparatus for associating metadata attributes with program elements
JP2004164555A (en) 2002-09-17 2004-06-10 Fuji Xerox Co Ltd Apparatus and method for retrieval, and apparatus and method for index building
US20040064442A1 (en) 2002-09-27 2004-04-01 Popovitch Steven Gregory Incremental search engine
US6886010B2 (en) 2002-09-30 2005-04-26 The United States Of America As Represented By The Secretary Of The Navy Method for data and text mining and literature-based discovery
US7085755B2 (en) 2002-11-07 2006-08-01 Thomson Global Resources Ag Electronic document repository management and access system
US20050060304A1 (en) 2002-11-19 2005-03-17 Prashant Parikh Navigational learning in a structured transaction processing system
US7257574B2 (en) 2002-11-19 2007-08-14 Prashant Parikh Navigational learning in a structured transaction processing system
US7386527B2 (en) 2002-12-06 2008-06-10 Kofax, Inc. Effective multi-class support vector machine classification
US20040117351A1 (en) 2002-12-14 2004-06-17 International Business Machines Corporation System and method for identifying and utilizing a secondary index to access a database using a management system without an internal catalogue of online metadata
US20040141354A1 (en) 2003-01-18 2004-07-22 Carnahan John M. Query string matching method and apparatus
US20040148278A1 (en) 2003-01-22 2004-07-29 Amir Milo System and method for providing content warehouse
RU2236699C1 (en) 2003-02-25 2004-09-20 Открытое акционерное общество "Телепортал. Ру" Method for searching and selecting information with increased relevance
JP2004265015A (en) 2003-02-28 2004-09-24 Toyota Infotechnology Center Co Ltd Content-retrieving index generation device
US20040181515A1 (en) 2003-03-13 2004-09-16 International Business Machines Corporation Group administration of universal resource identifiers with members identified in search result
US6947930B2 (en) 2003-03-21 2005-09-20 Overture Services, Inc. Systems and methods for interactive search query refinement
US20040186827A1 (en) 2003-03-21 2004-09-23 Anick Peter G. Systems and methods for interactive search query refinement
EP1462950B1 (en) 2003-03-27 2007-08-29 Sony Deutschland GmbH Method for language modelling
US20050033742A1 (en) 2003-03-28 2005-02-10 Kamvar Sepandar D. Methods for ranking nodes in large directed graphs
US7028029B2 (en) 2003-03-28 2006-04-11 Google Inc. Adaptive computation of ranking
RU2319202C2 (en) 2003-03-31 2008-03-10 Гугл Инк. System and method for providing preferred language for sorting search results
US20040194099A1 (en) 2003-03-31 2004-09-30 John Lamping System and method for providing preferred language ordering of search results
US7051023B2 (en) 2003-04-04 2006-05-23 Yahoo! Inc. Systems and methods for generating concept units from search queries
US7197497B2 (en) 2003-04-25 2007-03-27 Overture Services, Inc. Method and apparatus for machine learning a document relevance function
US7283997B1 (en) 2003-05-14 2007-10-16 Apple Inc. System and method for ranking the relevance of documents retrieved by a query
US20040249795A1 (en) 2003-06-05 2004-12-09 International Business Machines Corporation Semantics-based searching for information in a distributed data processing system
US7836391B2 (en) 2003-06-10 2010-11-16 Google Inc. Document search engine including highlighting of confident results
US20040254932A1 (en) 2003-06-16 2004-12-16 Vineet Gupta System and method for providing preferred country biasing of search results
US20040260695A1 (en) 2003-06-20 2004-12-23 Brill Eric D. Systems and methods to tune a general-purpose search engine for a search entry point
US7228301B2 (en) 2003-06-27 2007-06-05 Microsoft Corporation Method for normalizing document metadata to improve search results using an alias relationship directory service
US20040267722A1 (en) 2003-06-30 2004-12-30 Larimore Stefan Isbein Fast ranked full-text searching
US7308643B1 (en) 2003-07-03 2007-12-11 Google Inc. Anchor tag indexing in a web crawler system
US20050060186A1 (en) 2003-08-28 2005-03-17 Blowers Paul A. Prioritized presentation of medical device events
US20050060310A1 (en) 2003-09-12 2005-03-17 Simon Tong Methods and systems for improving a search ranking using population information
US20050060311A1 (en) 2003-09-12 2005-03-17 Simon Tong Methods and systems for improving a search ranking using related queries
US20050114324A1 (en) 2003-09-14 2005-05-26 Yaron Mayer System and method for improved searching on the internet or similar networks and especially improved MetaNews and/or improved automatically generated newspapers
JP2007507798A (en) 2003-09-30 2007-03-29 グーグル・インク System for scoring the methods and documents for ranking method, a document for scoring the document
US20050240580A1 (en) 2003-09-30 2005-10-27 Zamir Oren E Personalization of placed content ordering in search results
US20050071741A1 (en) 2003-09-30 2005-03-31 Anurag Acharya Information retrieval based on historical data
US20050071328A1 (en) 2003-09-30 2005-03-31 Lawrence Stephen R. Personalization of web search
US7346839B2 (en) 2003-09-30 2008-03-18 Google Inc. Information retrieval based on historical data
US20050086206A1 (en) 2003-10-15 2005-04-21 International Business Machines Corporation System, Method, and service for collaborative focused crawling of documents on a network
US20050086192A1 (en) 2003-10-16 2005-04-21 Hitach, Ltd. Method and apparatus for improving the integration between a search engine and one or more file servers
US20050089215A1 (en) 2003-10-25 2005-04-28 Carl Staelin Image artifact reduction using a neural network
US7231399B1 (en) 2003-11-14 2007-06-12 Google Inc. Ranking documents based on large data sets
US7844589B2 (en) 2003-11-18 2010-11-30 Yahoo! Inc. Method and apparatus for performing a search
US20050125392A1 (en) 2003-12-08 2005-06-09 Andy Curtis Methods and systems for providing a response to a query
US20060047649A1 (en) 2003-12-29 2006-03-02 Ping Liang Internet and computer information retrieval and mining with intelligent conceptual filtering, visualization and automation
US20050144162A1 (en) 2003-12-29 2005-06-30 Ping Liang Advanced search, file system, and intelligent assistant agent
US20050154710A1 (en) 2004-01-08 2005-07-14 International Business Machines Corporation Dynamic bitmap processing, identification and reusability
US20050154746A1 (en) 2004-01-09 2005-07-14 Yahoo!, Inc. Content presentation and management system associating base content and relevant additional content
EP1557770A1 (en) 2004-01-23 2005-07-27 Microsoft Corporation Building and using subwebs for focused search
US20050165753A1 (en) 2004-01-23 2005-07-28 Harr Chen Building and using subwebs for focused search
US20050165718A1 (en) 2004-01-26 2005-07-28 Fontoura Marcus F. Pipelined architecture for global analysis and index building
US20050165781A1 (en) 2004-01-26 2005-07-28 Reiner Kraft Method, system, and program for handling anchor text
JP2004192657A (en) 2004-02-09 2004-07-08 Nec Corp Information retrieval system, and recording medium recording information retrieval method and program for information retrieval
US20050192936A1 (en) 2004-02-12 2005-09-01 Meek Christopher A. Decision-theoretic web-crawling and predicting web-page change
US7281002B2 (en) 2004-03-01 2007-10-09 International Business Machine Corporation Organizing related search results
US20050192955A1 (en) 2004-03-01 2005-09-01 International Business Machines Corporation Organizing related search results
US20050210079A1 (en) 2004-03-17 2005-09-22 Edlund Stefan B Method for synchronizing documents for disconnected operation
US20050210006A1 (en) 2004-03-18 2005-09-22 Microsoft Corporation Field weighting in text searching
US20050210105A1 (en) 2004-03-22 2005-09-22 Fuji Xerox Co., Ltd. Conference information processing apparatus, and conference information processing method and storage medium readable by computer
US20050216533A1 (en) 2004-03-29 2005-09-29 Yahoo! Inc. Search using graph colorization and personalized bookmark processing
US20070276829A1 (en) 2004-03-31 2007-11-29 Niniane Wang Systems and methods for ranking implicit search results
US7580568B1 (en) 2004-03-31 2009-08-25 Google Inc. Methods and systems for identifying an image as a representative image for an article
US20050251499A1 (en) 2004-05-04 2005-11-10 Zezhen Huang Method and system for searching documents using readers valuation
US20050262050A1 (en) 2004-05-07 2005-11-24 International Business Machines Corporation System, method and service for ranking search results using a modular scoring system
US7257577B2 (en) 2004-05-07 2007-08-14 International Business Machines Corporation System, method and service for ranking search results using a modular scoring system
US20050256865A1 (en) 2004-05-14 2005-11-17 Microsoft Corporation Method and system for indexing and searching databases
US7260573B1 (en) 2004-05-17 2007-08-21 Google Inc. Personalizing anchor text scores in a search engine
US20050283473A1 (en) 2004-06-17 2005-12-22 Armand Rousso Apparatus, method and system of artificial intelligence for data searching applications
US7716225B1 (en) 2004-06-17 2010-05-11 Google Inc. Ranking documents based on user behavior and/or feature data
US20050289193A1 (en) 2004-06-25 2005-12-29 Yan Arrouye Methods and systems for managing data
US20050289133A1 (en) 2004-06-25 2005-12-29 Yan Arrouye Methods and systems for managing data
US7562068B2 (en) 2004-06-30 2009-07-14 Microsoft Corporation System and method for ranking search results based on tracked user preferences
US7243102B1 (en) 2004-07-01 2007-07-10 Microsoft Corporation Machine directed improvement of ranking algorithms
US7428530B2 (en) 2004-07-01 2008-09-23 Microsoft Corporation Dispersing search engine results by using page category information
US20060031183A1 (en) 2004-08-04 2006-02-09 Tolga Oral System and method for enhancing keyword relevance by user's interest on the search result documents
US20060041521A1 (en) 2004-08-04 2006-02-23 Tolga Oral System and method for providing graphical representations of search results in multiple related histograms
US20060036598A1 (en) 2004-08-09 2006-02-16 Jie Wu Computerized method for ranking linked information items in distributed sources
US20060047643A1 (en) 2004-08-31 2006-03-02 Chirag Chaman Method and system for a personalized search engine
US20060059144A1 (en) 2004-09-16 2006-03-16 Telenor Asa Method, system, and computer program product for searching for, navigating among, and ranking of documents in a personal web
US20060064411A1 (en) 2004-09-22 2006-03-23 William Gross Search engine using user intent
US7606793B2 (en) 2004-09-27 2009-10-20 Microsoft Corporation System and method for scoping searches using index keys
US8843486B2 (en) 2004-09-27 2014-09-23 Microsoft Corporation System and method for scoping searches using index keys
US20060069982A1 (en) 2004-09-30 2006-03-30 Microsoft Corporation Click distance determination
US20100268707A1 (en) 2004-09-30 2010-10-21 Microsoft Corporation System and method for ranking search results using click distance
US20060074871A1 (en) 2004-09-30 2006-04-06 Microsoft Corporation System and method for incorporating anchor text into ranking search results
JP4950444B2 (en) 2004-09-30 2012-06-13 マイクロソフト コーポレーション System and method for ranking search results using the click distance
US20060074903A1 (en) 2004-09-30 2006-04-06 Microsoft Corporation System and method for ranking search results using click distance
US7827181B2 (en) 2004-09-30 2010-11-02 Microsoft Corporation Click distance determination
US8082246B2 (en) 2004-09-30 2011-12-20 Microsoft Corporation System and method for ranking search results using click distance
KR20060048716A (en) 2004-09-30 2006-05-18 마이크로소프트 코포레이션 System and method for ranking search results using click distance
US7644107B2 (en) 2004-09-30 2010-01-05 Microsoft Corporation System and method for batched indexing of network documents
US20060074883A1 (en) 2004-10-05 2006-04-06 Microsoft Corporation Systems, methods, and interfaces for providing personalized search and information access
US20060173560A1 (en) 2004-10-07 2006-08-03 Bernard Widrow System and method for cognitive memory and auto-associative neural network based pattern recognition
US20060095416A1 (en) 2004-10-28 2006-05-04 Yahoo! Inc. Link-based spam detection
CN101180624A (en) 2004-10-28 2008-05-14 雅虎公司 Link-based spam detection
US20060136411A1 (en) * 2004-12-21 2006-06-22 Microsoft Corporation Ranking search results using feature extraction
US20060161534A1 (en) 2005-01-18 2006-07-20 Yahoo! Inc. Matching and ranking of sponsored search listings incorporating web search technology and web content
US20060173828A1 (en) 2005-02-01 2006-08-03 Outland Research, Llc Methods and apparatus for using personal background data to improve the organization of documents retrieved in response to a search query
US20060195440A1 (en) 2005-02-25 2006-08-31 Microsoft Corporation Ranking results using multiple nested ranking
US20060294100A1 (en) 2005-03-03 2006-12-28 Microsoft Corporation Ranking search results using language types
US20060200460A1 (en) 2005-03-03 2006-09-07 Microsoft Corporation System and method for ranking search results using file types
US20060206476A1 (en) 2005-03-10 2006-09-14 Yahoo!, Inc. Reranking and increasing the relevance of the results of Internet searches
US20060206460A1 (en) 2005-03-14 2006-09-14 Sanjay Gadkari Biasing search results
US20060212423A1 (en) * 2005-03-16 2006-09-21 Rosie Jones System and method for biasing search results based on topic familiarity
US20070106659A1 (en) 2005-03-18 2007-05-10 Yunshan Lu Search engine that applies feedback from users to improve search results
US20060224554A1 (en) 2005-03-29 2006-10-05 Bailey David R Query revision using known highly-ranked queries
US7693829B1 (en) 2005-04-25 2010-04-06 Google Inc. Search engine with fill-the-blanks capability
US20060248074A1 (en) 2005-04-28 2006-11-02 International Business Machines Corporation Term-statistics modification for category-based search
WO2006121269A1 (en) 2005-05-06 2006-11-16 Nhn Corporation Personalized search method and system for enabling the method
KR20060116042A (en) 2005-05-09 2006-11-14 엔에이치엔(주) Personalized search method using cookie information and system for enabling the method
US20060259481A1 (en) 2005-05-12 2006-11-16 Xerox Corporation Method of analyzing documents
US7962462B1 (en) 2005-05-31 2011-06-14 Google Inc. Deriving and using document and site quality signals from search query streams
US20060282306A1 (en) 2005-06-10 2006-12-14 Unicru, Inc. Employee selection via adaptive assessment
US20060282455A1 (en) 2005-06-13 2006-12-14 It Interactive Services Inc. System and method for ranking web content
US20060287993A1 (en) 2005-06-21 2006-12-21 Microsoft Corporation High scale adaptive search systems and methods
US20070038616A1 (en) 2005-08-10 2007-02-15 Guha Ramanathan V Programmable search engine
US20070038622A1 (en) 2005-08-15 2007-02-15 Microsoft Corporation Method ranking search results using biased click distance
US20070050338A1 (en) 2005-08-29 2007-03-01 Strohm Alan C Mobile sitemaps
US20100191744A1 (en) 2005-09-21 2010-07-29 Dmitriy Meyerzon Ranking functions using document usage statistics
US20070067284A1 (en) 2005-09-21 2007-03-22 Microsoft Corporation Ranking functions using document usage statistics
US7499919B2 (en) 2005-09-21 2009-03-03 Microsoft Corporation Ranking functions using document usage statistics
US20070073748A1 (en) 2005-09-27 2007-03-29 Barney Jonathan A Method and system for probabilistically quantifying and visualizing relevance between two or more citationally or contextually related data objects
US7716226B2 (en) 2005-09-27 2010-05-11 Patentratings, Llc Method and system for probabilistically quantifying and visualizing relevance between two or more citationally or contextually related data objects
US7689531B1 (en) 2005-09-28 2010-03-30 Trend Micro Incorporated Automatic charset detection using support vector machines with charset grouping
US20070085716A1 (en) 2005-09-30 2007-04-19 International Business Machines Corporation System and method for detecting matches of small edit distance
US20070094285A1 (en) 2005-10-21 2007-04-26 Microsoft Corporation Question answering over structured content on the web
US20070150473A1 (en) 2005-12-22 2007-06-28 Microsoft Corporation Search By Document Type And Relevance
WO2007089289A2 (en) 2006-01-31 2007-08-09 Louis Wang Method for ranking and sorting electronic documents in a search result list based on relevance
US7689559B2 (en) 2006-02-08 2010-03-30 Telenor Asa Document similarity scoring and ranking method, device and computer program product
US20070198459A1 (en) 2006-02-14 2007-08-23 Boone Gary N System and method for online information analysis
WO2007123416A1 (en) 2006-04-24 2007-11-01 Telenor Asa Method and device for efficiently ranking documents in a similarity graph
WO2007149623A2 (en) 2006-04-25 2007-12-27 Infovell, Inc. Full text query and search systems and method of use
US20070260597A1 (en) 2006-05-02 2007-11-08 Mark Cramer Dynamic search engine results employing user behavior
EP1862916A1 (en) 2006-06-01 2007-12-05 Microsoft Corporation Indexing Documents for Information Retrieval based on additional feedback fields
US20080005068A1 (en) 2006-06-28 2008-01-03 Microsoft Corporation Context-based search, retrieval, and awareness
US20080016053A1 (en) 2006-07-14 2008-01-17 Bea Systems, Inc. Administration Console to Select Rank Factors
JP2008033931A (en) 2006-07-26 2008-02-14 Xerox Corp Method for enrichment of text, method for acquiring text in response to query, and system
US7720830B2 (en) * 2006-07-31 2010-05-18 Microsoft Corporation Hierarchical conditional random fields for web extraction
KR20080017685A (en) 2006-08-22 2008-02-27 에스케이커뮤니케이션즈 주식회사 Document ranking granting method and computer readable record medium thereof
KR20080024584A (en) 2006-09-14 2008-03-19 엔에이치엔(주) Method for making document score using book search and system for executing the method
US20080140641A1 (en) 2006-12-07 2008-06-12 Yahoo! Inc. Knowledge and interests based search term ranking for search results validation
US20080154888A1 (en) 2006-12-11 2008-06-26 Florian Michel Buron Viewport-Relative Scoring For Location Search Queries
JP2008146424A (en) 2006-12-12 2008-06-26 Nippon Telegr & Teleph Corp <Ntt> Xml document conformity calculation method, its program, and information processor
US7685084B2 (en) 2007-02-09 2010-03-23 Yahoo! Inc. Term expansion using associative matching of labeled term pairs
US20080195596A1 (en) 2007-02-09 2008-08-14 Jacob Sisk System and method for associative matching
US8412717B2 (en) 2007-06-27 2013-04-02 Oracle International Corporation Changing ranking algorithms based on customer settings
US20090006358A1 (en) 2007-06-27 2009-01-01 Microsoft Corporation Search results
US20090006356A1 (en) 2007-06-27 2009-01-01 Oracle International Corporation Changing ranking algorithms based on customer settings
US20090024606A1 (en) 2007-07-20 2009-01-22 Google Inc. Identifying and Linking Similar Passages in a Digital Text Corpus
US20090070306A1 (en) 2007-09-07 2009-03-12 Mihai Stroe Systems and Methods for Processing Inoperative Document Links
US8909655B1 (en) 2007-10-11 2014-12-09 Google Inc. Time based ranking
US7840569B2 (en) 2007-10-18 2010-11-23 Microsoft Corporation Enterprise relevancy ranking using a neural network
US20090106235A1 (en) 2007-10-18 2009-04-23 Microsoft Corporation Document Length as a Static Relevance Feature for Ranking Search Results
US7836048B2 (en) 2007-11-19 2010-11-16 Red Hat, Inc. Socially-derived relevance in search engine results
WO2009072174A1 (en) 2007-12-03 2009-06-11 Pioneer Corporation Information retrieval apparatus, method for information retrieval, and retrieval processing program
US8165406B2 (en) 2007-12-12 2012-04-24 Microsoft Corp. Interactive concept learning in image search
US20090157607A1 (en) 2007-12-12 2009-06-18 Yahoo! Inc. Unsupervised detection of web pages corresponding to a similarity class
JP2009146248A (en) 2007-12-17 2009-07-02 Fujifilm Corp Content presenting system and program
US20090164929A1 (en) 2007-12-20 2009-06-25 Microsoft Corporation Customizing Search Results
JP2009204442A (en) 2008-02-28 2009-09-10 Athlete Fa Kk Weighing device for particulate matter
US8412702B2 (en) 2008-03-12 2013-04-02 Yahoo! Inc. System, method, and/or apparatus for reordering search results
US20090240680A1 (en) * 2008-03-20 2009-09-24 Microsoft Corporation Techniques to perform relative ranking for search results
JP2009252179A (en) 2008-04-10 2009-10-29 Ntt Docomo Inc Recommendation information evaluation device and recommendation information evaluation method
US20090259651A1 (en) 2008-04-11 2009-10-15 Microsoft Corporation Search results ranking using editing distance and document information
US8126883B2 (en) 2008-05-04 2012-02-28 Gang Qiu Method and system for re-ranking search results
US20090276421A1 (en) 2008-05-04 2009-11-05 Gang Qiu Method and System for Re-ranking Search Results
US20090307209A1 (en) 2008-06-10 2009-12-10 David Carmel Term-statistics modification for category-based search
WO2010031085A2 (en) 2008-09-10 2010-03-18 Microsoft Corporation Document length as a static relevance feature for ranking search results
CN101360074A (en) 2008-09-27 2009-02-04 腾讯科技(深圳)有限公司 Method and system determining suspicious spam range
US8326829B2 (en) 2008-10-17 2012-12-04 Centurylink Intellectual Property Llc System and method for displaying publication dates for search results
US20110106850A1 (en) 2009-10-29 2011-05-05 Microsoft Corporation Relevant Individual Searching Using Managed Property and Ranking Features
US20110137893A1 (en) 2009-12-04 2011-06-09 Microsoft Corporation Custom ranking model schema
US20110235909A1 (en) 2010-03-26 2011-09-29 International Business Machines Corporation Analyzing documents using stored templates
US20110295850A1 (en) 2010-06-01 2011-12-01 Microsoft Corporation Detection of junk in search result ranking
US8370331B2 (en) 2010-07-02 2013-02-05 Business Objects Software Limited Dynamic visualization of search results on a graphical user interface
US20130198174A1 (en) 2012-01-27 2013-08-01 Microsoft Corporation Re-ranking search results

Non-Patent Citations (520)

* Cited by examiner, † Cited by third party
Title
"Microsoft External Content in Microsoft Office SharePoint Portal Server 2003", http://www.microsoft.com/technet/prodtechnol/sppt/reskit/c2261881x.mspx, published on Jun. 9, 2004, printed on May 22, 2006, 20 pp.
"Microsoft FAST Search Server 2010 for SharePoint, Evaluation Guide", Published on Aug. 12, 2010, Available at: http://www.microsoft.com/downloads/info.aspx?na=41&srcfamilyid=f1e3fb39-6959-4185-8b28-5315300b6e6b&srcdisplaylang=en&u=http%3a%2f%2download.microsoft.com%2fdownload%2fA%2f7 %2fF%2fA7F98D88-BC15-4F3C-8B71-D42A5ED79964%, 60 pgs.
"Microsoft Full-Text Search Technologies", http://www.microsoft.com/technet/prodtechnol/sppt/sharepoint/evaluate/featfunc/mssearc . . . , published on Jun. 1, 2001, printed on May 22, 2006, 13 pp.
"Microsoft SharePoint Portal Server 2001 Resource Kit: Chapter 24, Analyzing the Default Query for the Dashboard", http://www.microsoft.com/technet/prodtechnol/sppt/sharepoint/reskit/part5/c24spprk.mspx, printed on May 22, 2006, 5 pp.
"Planning Your Information Structure Using Microsoft Office SharePoint Portal Server 2003", http://www.microsoft.com/technet/prodtechnol/sppt/reskit/c0861881x.mspx, published on Jun. 9, 2004, printed on May 22, 2006, 22 pp.
"SharePoint Portal Server 2001 Planning and Installation Guide", http://www.microsoft.com/technet/prodtechnol/sppt/sharepoint/plan/planinst.mspx, printed on May 22, 2006, 86 pp.
Agarwal et al., "Ranking Database Queries Using User Feedback: A Neural Network Approach", Fall 2006, 9 pp.
Agichtein, Eugene et al., "Improving web search ranking by incorporating user behavior information", Proceedings of the Twenty-Ninth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval ACM New York, NY, USA, vol. 29, Aug. 6, 2006, pp. 19-26.
Agichten et al., "Improving Web Search Ranking by Incorporating User Behavior Information"-http://www.mathcs.emory.edu/ ~eugene/papers/sigir2006ranking.pdf, 8 pp.
Agichten et al., "Improving Web Search Ranking by Incorporating User Behavior Information"-http://www.mathcs.emory.edu/ ˜eugene/papers/sigir2006ranking.pdf, 8 pp.
Amit Singhal et al., Document Length Normalization, 1996, Cornell University, vol. 32, No. 5, pp. 619-633. *
Australian Exam Report in Application No. 2008 00521-7, mailed Mar. 11, 2009, 4 pgs.
Australian First Examiner's Report in 2006279520 mailed Oct. 5, 2010.
Australian Lapsing Notice in Application 2009290574, mailed May 19, 2014, 1 page.
Australian Notice of Allowance in Application 2006279520, mailed Mar. 2, 2011, 3 pgs.
Australian Notice of Allowance in Application 2009234120, mailed May 8, 2014, 2 pgs.
Australian Notice of Allowance in Application 2009290574, mailed Jan. 16, 2015, 2 pgs.
Australian Office Action in Application 2009234120, mailed Feb. 26, 2014, 3 pgs.
Australian Office Action in Application 2009290574, mailed Dec. 3, 2014, 3 pgs.
Bandinelli, Luca, "Using Microsoft SharePoint Products and Technologies in Multilingual Scenarios", http://www.microsoft.com/technet/prodtechnol/office/sps2003/maintain/spmultil.mspx, published on Nov. 1, 2003, printed on May 22, 2006, 32 pp.
Becker, Hila et al., "Learning Similarity Metrics for Event Identification in Social Media," Published Date: Feb. 4-6, 2010, http://infolab.stanford.edu/˜mor/research/becker-wsdm10.pdf, 10 pgs.
Bohm et al., "Multidimensional Index Structures in Relational Databases", Journal of Intelligent Information Systems, Jul. 2000, vol. 15, Issue 1, pp. 1-20, found at: http://springerlink.com/content/n345270t27538741/fulltext.pdf.
Brin, S. et al., "The Anatomy of a Large-Scale Hypertextual Web Search Engine", Proceedings of the Seventh International World-Wide Web Conference, ′Online! Apr. 14, 1998, pp. 1-26.
Brin, S. et al., "The Anatomy of a Large-Scale Hypertextual Web Search Engine", Proceedings of the Seventh International World-Wide Web Conference, 'Online! Apr. 14, 1998, pp. 1-26.
C. Burges, R. Ragno, Q. V. Le, "Learning To Rank With Nonsmooth Cost Functions," http://research.microsoft.com/˜cburges/papers/lambdarank.pdf, Schölkopf, Platt and Hofmann (Ed.) Advances in Neural Information Processing Systems 19, Proceedings of the 2006 Conference, MIT Press, 2006, 8 pages.
Canadian Notice of Allowance in Application 2618854, received Jan. 13, 2014, 1 pg.
Canadian Office Action in Application 2618854, mailed Mar. 27, 2013, 2 pgs.
Carmel, D. et al., "Searching XML Documents Via XML Fragments", SIGIR Toronto, Canada, Jul.-Aug. 2003, pp. 151-158.
Chakrabarti, S., "Recent Results in Automatic Web Resource Discovery", ACM Computing Surveys, vol. 31, No. 4es, Dec. 1999, pp. 1-7.
Chen, Hsinchun et al., "A Smart Itsy Bitsy Spider for the Web", Journal of the American Society for Information Science, 49(7), 1998, pp. 604-618.
Chen, Michael et al., Cha Cha, "A System for Organizing Intranet Search Results", Computer Science Department, University of California, Berkeley, 1999, pp. 1-12.
Chinese 1st Office Action in Application 200980112928.6, mailed Jun. 8, 2012, 8 pgs.
Chinese 1st Office Action in Application 201180027027.4, mailed Dec. 29, 2014, 11 pgs.
Chinese 2nd Office Action in Application 200980112928.6, mailed Mar. 4, 2013, 9 pgs.
Chinese Application 200510088213.5, Notice of Allowance mailed Apr. 20, 2010, 4 pgs.
Chinese Application No. 200510088212.0, First Office Action mailed Jul. 4, 2008, 10 pgs.
Chinese Application No. 200510088212.0, Notice of Allowance mailed Jan. 8, 2010, 4 pgs.
Chinese Decision on Reexamination cited in 200680029645.1, mailed Dec. 14, 2012, 15 pgs.
Chinese Decision on Re-Examination in Application 200510084707.6 mailed Aug. 22, 2011, 12 pgs.
Chinese Decision on Rejection in 200680029645.1 mailed Aug. 12, 2010.
Chinese Final Rejection in 200510084707.6 mailed Aug. 21, 2009, 13 pgs.
Chinese Final Rejection mailed Mar. 6, 2009 in Chinese Application No. 200510088213.5.
Chinese First Office Action in 200510084707.6 mailed Mar. 28, 2008, 10 pgs.
Chinese First Office Action in 200510088213.5 mailed May 9, 2008.
Chinese First Office Action in 200510088527.5 mailed Apr. 18, 2008.
Chinese First Office Action in 200680034531.6 mailed Sep. 11, 2009, 7 pgs.
Chinese First Office Action in Chinese Application/Patent No. 200880112416.5, mailed Aug. 12, 2011, 11 pgs.
Chinese First Official Action in 200680029645.1 mailed Jun. 19, 2009.
Chinese First Official Action in 200680035828.4 mailed Jun. 19, 2009.
Chinese Notice of Allowance in 200510088527.5 mailed Jul. 24, 2009, 4 pgs.
Chinese Notice of Allowance in 200680034531.6 mailed Oct. 14, 2010, 6 pgs.
Chinese Notice of Allowance in Application 200510084707.6, mailed Sep. 25, 2012, 4 pgs.
Chinese Notice of Allowance in Application 200880112416.5, mailed Jul. 18, 2012,4 pgs.
Chinese Notice of Allowance in Application 2009801129286, mailed Aug. 30, 2013, 4 pgs.
Chinese Notice of Allowance in Application 201180027027.4, mailed Aug. 27, 2015, 4 pgs.
Chinese Notice of Reexamination in Application 200680029645.1, mailed Aug. 20, 2012, 11 pgs.
Chinese Second Office Action in 200510084707.6 mailed Nov. 7, 2008, 10 pgs.
Chinese Second Office Action in 200510088213.5 mailed Oct. 10, 2008.
Chinese Second Official Action in 200510088527.5 mailed Dec. 26, 2008.
Chinese Third Office Action in 200510084707.6 mailed Feb. 20, 2009, 12 pgs.
Chinese Third Official Action in 200510088213.5 mailed Sep. 4, 2009.
Cho et al., "Efficient Crawling Through URL Ordering", In Proceedings of the 7th International World Wide Web Conference, Apr. 1998, pp. 161-180.
Conlon, M., "Inserts Made Simple", American Printer, Nov. 1, 2002, 4 pages.
Craswell, N. et al., "TREC12 Web Track as CSIRO", TREC 12, Nov. 2003, 11 pp.
Craswell, Nick et al., "Relevance Weighting for Query Independent Evidence", Aug. 15-19, 2005, ACM, pp. 416-423.
Cutler, M. et al., "A New Study on Using HTML Structures to Improve Retrieval", 11th IEEE International Conference on Chicago, IL, Nov. 9-11, 1999, pp. 406-409.
Desmet, P. et al., "Estimation of Product Category Sales Responsiveness to Allocated Shelf Space", Intern. J. of Research in Marketing, vol. 15, No. 5, Dec. 9, 1998, pp. 443-457.
Ding, Chen et al., "An Improved Usage-Based Ranking", obtained online Jul. 1, 2009 at: http://www.springerlink.com/content/h0jut6d1dnrk5227/fulltext.pdf, 8 pgs.
Egyptian Official Action in PCT 269/2008 mailed Feb. 1, 2010.
Egyptian Official Action in PCT 269/2008 mailed Mar. 17, 2010, 2 pgs.
Eiron, N. et al., "Analysis of Anchor Text for Web Search", Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul. 28-Aug. 1, 2003, Toronto, Canada, 8 pgs.
EP 00309121.2 Summon to attend oral proceedings pursuant to Rule 115(1) EPC mailed Mar. 11, 2009, 11 pgs.
EP 05105110.0, Office Action mailed Sep. 18, 2006, 2 pgs.
EP Communication to cancel the oral summons in Application 05105048.2, mailed Jul. 16, 2012, 1 pg.
EP Exam Report in EP 00309121.2-1522 mailed Jul. 4, 2003.
EP Exam Report in EP 00309121.2-1527 mailed Feb. 8, 2007.
EP Exam Report in EP 00309121.2-1527 mailed Jun. 16, 2004.
EP Exam Report in EP 05105048.2-2201 mailed Apr. 23, 2007.
EP Examination Report in Application 05105672.9, mailed Oct. 24, 2006, 4 pgs.
EP Notice of Allowance in Application 05105048.2, mailed Aug. 13, 2012, 8 pgs.
EP Office Action in Application 05105107.6, mailed Mar. 28, 2008, 6 pgs.
EP Result of consultation in Application 05105048.2, mailed Aug. 8, 2012, 3 pgs.
EP Search Report in Application 05105107.6, mailed Apr. 7, 2006, 3 pgs.
EP Search Report in Application 05105672.9, mailed Feb. 6, 2006, 3 pgs.
EP Search Report in EP 00309121 mailed Jul. 18, 2002.
EP Search Report in EP 05105048 mailed Jan. 17, 2006.
EP Search Report in EP 05105110 dated Aug. 11, 2006.
EP Second Office Action in Application 05105672.9, mailed Oct. 15, 2009, 4 pgs.
EP Summons to Attend Oral Proceedings in EP 05105048.2-2201 mailed Apr. 3, 2012.
European Brief Communication in Application 05105672.9, mailed Dec. 21, 2015, 1 page.
European Communication in Application 05105107.6, mailed Dec. 17, 2012, 4 pgs.
European Communication in Application 06789800.7, mailed Oct. 23, 2014, 9 pgs.
European Extended Search Report in Application 06836141.9 mailed Dec. 27, 2011, 8 pgs.
European Extended Search Report in Application 097308084, mailed Oct. 2, 2012, 7 pgs.
European extended Search Report in Application 09813811.8, mailed Mar. 3, 2016, 8 pgs.
European Intention to Grant in Application 09730808.4, mailed Nov. 7, 2014, 7 pgs.
European Notice of Allowance in Application 00309121.2, mailed Jun. 15, 2009, 5 pgs.
European Notice of Allowance in Application EP 06836141.9, mailed Jan. 31, 2013, 6 pgs.
European Official Action in 05105110.0-1527, Aug. 4, 2010, 6 pages.
European Report on Result of Consultation in Application EP 06836141.9, mailed Jan. 9, 2013, 3 pgs.
European Search Report in Application 06789800.7 mailed Oct. 13, 2011, 11 pgs.
European Summons to attend oral proceedings in Application 05105672.9, mailed Dec. 21, 2015, 1 page.
European Summons to Attend Oral Proceedings in Application 05105672.9, mailed Nov. 30, 2015, 1 page.
European Summons to Attend Oral Proceedings in Application 05105672.9, mailed Nov. 6, 2015, 7 pgs.
Extended European Search Report in Application 06804098.9, mailed Dec. 19, 2011, 7 pgs.
Fagin, R. et al., "Searching the Workplace Web", IBM Almaden Research Center, In Proceedings of the Twelfth International World Wide Web Conference, Budapest, 2003, 21 pgs.
Fagin, Ronald, "Searching the Workplace Web", Mar. 3, 2005, pp. 1-10.
Fiedler, J. et al., Using the Web Efficiently: Mobile Crawlers, 17th Annual Int'l. Conference of the Association of Management on Computer Science, Aug. 1999, pp. 324-329.
Final Office Action in U.S. Appl. No. 11/874,579 mailed Jan. 14, 2011.
Gross, Christian, "This is Site Server! Integrating The Microsoft Index Server with Active Server Pages", printed in Microsoft Interactive Developer, Jul. 1997, No. 2, published by ASCII Corporation, Japan, on Jul. 18, 1997, pp. 75-90. (no English translation).
Gross, Christian, Microsoft Interactive Developer, No. 2, "Integrating the Microsoft Index Server with Active Server Pages", Jun. 1997, 21 pgs.
Hawking, D. et al., "Overview of the TREC-8 Web Track", TREC, Feb. 2000, pp. 1-18.
Hawking, D., "Overview of the TREC-9 Track", TREC, 2000, pp. 1-16.
Hawking., D. et al., "Overview of TREC-7 Very Large Collection Track", TREC, Jan. 1999, pp. 1-13.
Heery, Rachel, "Review of Metadata Formats", Program, vol. 30, No. 4, Oct. 1996, 1996 IEEE, pp. 345-373.
Hiemstra, D. et al., "Relevance Feedback for Best Match Term Weighting Algorithms in Information Retrieval", Proceedings of the Joint DELOS-NSF Workshop on Personalisation and Recommender Systems in Digital Libraries, ERCIM Workshop Proceedings 01/W03, pp. 37-42, Jun. 2001.
Hoeber, Orland et al., "Evaluating the Effectiveness of Term Frequency Histograms for Supporting Interactive Web Search Tasks," Published Date: Feb. 25-27, 2008, http://delivery.acm.org/10.1145/1400000/1394484/p360-hoeber.pdf?key1=1394484&key2=1611170721&coll=GUIDE&dl=GUIDE&CFID=83362159&CFTOKEN=63982632, 9 pgs.
Horikawa, Akira, "Table design correcting room of Access user", Visual Basic Magazine, vol. 6, No. 3, pp. 158-170, Shoeisha Col. Ltd., Japan, Mar. 1, 2000. (No English translation available).
Huang et al., "Design and Implementation of a Chinese Full-Text Retrieval System Based on Probabilistic Model", IEEE, 1993, pp. 1090-1093.
Huuhka, "Google: Data Structures and Algorithms".
Indian Hearing Notice on Application 2260/DELNP/2008, mailed Jan. 29, 2016, 2 pgs.
Indian Office Action in Application 1479/DEL/2005, mailed Sep. 30, 2014, 2 pgs.
Indian Office Action in Application 1481/DEL/2005, mailed Sep. 30, 2014, 2 pgs.
Indian Office Action in Application 1484/DEL/2005, mailed Oct. 5, 2015, 2 pgs.
Indian Office Action in Application 1569/DEL/2005, mailed Sep. 12, 2014, 2 pgs.
Indian Office Action in Application 2260/DELNP/2008, mailed Sep. 22, 2015, 3 pgs.
Indonesian Notice of Allowance in Application W00200800848 mailed Jun. 9, 2011, 4 pgs.
International Preliminary Report on Patentability Issued in PCT Application No. PCT/US2009/63333, Mailed Date: Mar. 15, 2011, 4 Pages.
International Search Report cited in European Patent Application No. 08 840 594.9 Jan. 21, 2011, 8 pages.
Israel Office Action in Application 210591, mailed Feb. 23, 2016, 8 pgs.
Israeli Office Action in Application 207830, mailed Dec. 22, 2013, 7 pgs.
Israeli Office Action in Application 210591, mailed Oct. 23, 2014, 6 pgs.
Japanese Appeal Decision and Notice of Allowance in Application 2005-175174, mailed Jun. 18, 2013, 4 pgs.
Japanese Appeal Decision in 2008-527094 (Appeal No. 2010-011037) mailed Nov. 4, 2011-31 pgs., only first page translated.
Japanese Final Notice of Reason for Rejection in Application 2011-527079, mailed May 15, 2014, 6 pgs.
Japanese Final Notice of Rejection in Application No. 2005-187816 mailed Mar. 16, 2012, 5 pgs.
Japanese Final Rejection in 2005-175172 mailed Jun. 7, 2011, 5 pgs.
Japanese Final Rejection in Application 2011-266249, mailed Apr. 7, 2014, 4 pgs.
Japanese Final Rejection in JP Application 2008-532469, mailed Jan. 29, 2010, 19 pgs.
Japanese Final Rejection mailed Jan. 22, 2010 in JP Appln No. 2008/527094.
Japanese Interrogation in Application 2005-175174, mailed Jul. 24, 2012, 7 pgs.
Japanese Notice of Allowance in 2005-175172 mailed Mar. 6, 2012, 6 pgs.
Japanese Notice of Allowance in 2005-175173 mailed Jun. 7, 2011, 6 pgs.
Japanese Notice of Allowance in Application 2011-021985, mailed Dec. 25, 2012, 6 pgs.
Japanese Notice of Allowance in Application 2011-194741, mailed Sep. 6, 2013, 4 pgs.
Japanese Notice of Allowance in Application 2011-504031, mailed Jan. 30, 2014, 4 pgs.
Japanese Notice of Allowance in JP Application 2008-532469, mailed Feb. 22, 2011, 6 pgs.
Japanese Notice of Final Rejection in 2005-175174, mailed Aug. 5, 2011, 5 pgs.
Japanese Notice of Rejection in 2005-175172 mailed Sep. 28, 2010.
Japanese Notice of Rejection in 2005-175173 mailed Oct. 1, 2010.
Japanese Notice of Rejection in 2005-175174, mailed Oct. 29, 2010, 13 pgs.
Japanese Notice of Rejection in 2008-527094 mailed Sep. 11, 2009.
Japanese Notice of Rejection in Application 2011-194741, mailed May 14, 2013, 4 pgs.
Japanese Notice of Rejection in Application 2011-266249, mailed Sep. 2, 2013, 7 pgs.
Japanese Notice of Rejection in Application 2011-504031, mailed May 14, 2013, 4 pgs.
Japanese Notice of Rejection in Application 2011-527079, mailed Oct. 8, 2013, 15 pgs.
Japanese Notice of Rejection in Application No. 2005-187816 mailed May 20, 2011, 13 pgs.
Japanese Office Action in JP Application 2008-532469, mailed Sep. 29, 2009, 18 pgs.
Jien Yun Nie, Introduction to information retrieval, 1989, University of Montreal Canada, pp. 1-11. *
Jones, K. et al., "A probabilistic model of information retrieval: development and status", Department of Information Science, City University, London, Aug. 1998, 74 pgs.
K. L. Kwok, A Network Approach to Probabilistic Information Retrieval, Jul. 1995, ACM Transactions on Information Systems, vol. 13, No. 3, pp. 324-353. *
Kazama, K., "A Searching and Ranking Scheme Using Hyperlinks and Anchor Texts", IPSJ SIG Technical Report, vol. 2000, No. 71, Information Processing Society of Japan, Japan, Jul. 28, 2000, pp. 17-24.
Kleinberg, Jon M., "Authoritative Sources in a Hyperlinked Environment", Proceedings of the aCM-SIAM symposium on Discrete Algorithms, 1998, 34 pp.
Korean Notice of Preliminary Rejection in Application 10-2005-0056700, Feb. 16, 2010, 5 pgs. (no English translation).
Korean Notice of Preliminary Rejection in Application 10-2005-005719, Aug. 29, 2011, 1 page.
Korean Notice of Preliminary Rejection in Application 10-2005-005719, Mar. 26, 2012, 3 pgs. (no English translation).
Korean Notice of Preliminary Rejection in Application 10-2005-0057859, Feb. 11, 2010, 7 pgs. (no English translation).
Korean Notice of Preliminary Rejection in Application 10-2008-7003121, Jan. 24, 2013, 1 pg.
Korean Notice of Preliminary Rejection in Application 10-2008-7003121, mailed Jan. 21, 2013, 11 pgs.
Korean Notice of Preliminary Rejection in Application 1020087006775, mailed Feb. 4, 2013, 1 pg.
Korean Notice of Preliminary Rejection in Application 10-2008-7007702, mailed Feb. 4, 2013, 4 pgs.
Korean Notice of Preliminary Rejection in Application 10-2010-7022177, mailed Dec. 23, 2014, 9 pgs.
Korean Office Action in Application 10-2011-7005588, mailed Oct. 15, 2015, 9 pgs.
Korean Official Action in 2005-0057199 mailed Aug. 4, 2011, 4 pgs.
Korean Official Action in 2005-0057199 mailed Mar. 26, 2012, 5 pgs.
Kotsakis, E., "Structured Information Retrieval in XML Documents", Proceedings of the ACM Symposium on Applied Computing, Madrid, Spain, 2002, pp. 663-667.
Kucuk, Mehmet Emin, et al., "Application of Metadata Concepts to Discovery of Internet Resources", ADVIS 2000, INCS 1909, pp. 304-313, 2000.
Lalmas, M., "Uniform Representation of Content and Structure for Structured Document Retrieval", 20th SGES International Conference on Knowledge Based Systems and Applied Artificial Intelligence, Cambridge, UK, Dec. 2000, pp. 1-12.
Lam et al., "Automatic Document Classification Based on Probabilistic Reasoning: Model and Performance Analysis", IEEE, 1997, pp. 2719-2723.
Larkey, Leah S., et al., "Collection Selection and Results Merging with Topically Organized U.S. Patents and TREC Data", Proceedings of the Ninth International Conference on Information Knowledge Management, CIKM 2000, Nov. 6-11, 2000, pp. 282-289.
Lee, J.K.W. et al., "Intelligent Agents for Matching Information Providers and Consumers on the World-Wide Web", IEEE, 1997, pp. 189-199.
Lewandowski, Dirk, "Web searching, search engines and information retrieval", Information Services & Use, 2005, pp. 137-147, Retrieved from the Internet: URL:http://citeseerx.ist.psu.edu/viewdoc/download?doi=.10.1.1.301.3944&rep=rep1&type=pdf, retrieved Feb. 23, 2016.
Ljosland, Mildrid, "Evaluation of Web Search Engines and the Search for Better Ranking Algorithms," http://www.aitel.hist.no/˜mildrid/dring/paper/SIGIR.html, SIGIR99 Workshop on Evaluation of Reb Retrieval, Aug. 19, 1999, 5 pages.
Losee, R. et al., "Research in Information Organization", Literature Review, School of Information and Library Science, Section 4, pp. 53-96, Jan. 2001.
Losee, Robert M. et al., "Measuring Search Engine Quality and Query Difficulty: Ranking with Target and Freestyle," http://ils.unc.edu/˜losee/paril.pdf, Journal of the American Society for Information Science, Jul. 29, 1999, 20 pages.
Luxenburger et al., "Matching Task Profiles and User Needs in Personalized Web Search", CIKM Proceeding of the 17th ACM Conference on Information and Knowledge Mining, Oct. 2008, pp. 689-698.
Malaysia Adverse Report in Application PI20063920, mailed Jul. 31, 2012, 3 pgs.
Malaysia Adverse Search Report in Application PI20080638, mailed Jul. 31, 2012, 4 pgs.
Malaysian Notice of Allowance in Application PI 20080638, mailed Jun. 28, 2013, 2 pgs.
Malaysian Notice of Allowance in Application PI20063920, mailed Dec. 14, 2012, 2 pgs.
Malaysian Substantive Examination Report in Application PI 20063920, mailed Jul. 31, 2012, 3 pgs.
Manning, C. et al., "CS276A Text Information Retrieval, Mining, and Exploitation: Lecture 12", Stanford University CS276A/SYMBSYS2391/LING2391 Test Information Retrieval, Mining, and Exploitation, Fall 2002, last modified Nov. 18, 2002, 8 pgs.
Matsuo, Y., "A New Definition of Subjective Distance Between Web Pages," IPSJ Journal, vol. 44, No. 1, Information Processing Society of Japan, Japan, Jan. 15, 2003, pp. 88-94.
Matveeva, Irina, et al., "High Accuracy Retrieval with Multiple Nested Ranker," http://people.cs.uchicago.edu/~matveeva/RankerSIGIR06.pdf, SIGIR'06, Seattle, WA Aug. 6-11, 2006, 8 pages.
Matveeva, Irina, et al., "High Accuracy Retrieval with Multiple Nested Ranker," http://people.cs.uchicago.edu/˜matveeva/RankerSIGIR06.pdf, SIGIR'06, Seattle, WA Aug. 6-11, 2006, 8 pages.
Mexican Office Action with Summary in PA/a/2008/02173 mailed Jun. 5, 2012, 7 pgs.
Microsoft SharePoint Portal Server 2001 White Paper, "Microsoft SharePoint Portal Server: Advanced Technologies for Information Search and Retrieval," http://download.microsoft.com/download/3/7/a/37a762d7-dbe6-4b51-a6ec-f6136f44fd65/SPS-Search.doc, Jun. 2002, 12 pages.
Mittal et al., "Framework for Synthesizing Semantic-Level Indices", Multimedia Tools and Applications, Jun. 2003, vol. 20, Issue 2., pp. 1-24, found online at: http://www.springerlink.com/content/tv632274r1267305/fulltext.pdf.
MSDN, "Understanding Ranking," http://msdn.microsoft.com/en-us/library/ms142524.aspx, Sep. 2007, 4 pages.
Murata, Shin Ya, et al., "Ranking Search Results based on Information Needs in Conjunction with Click-Log Analysis", Journal of Japan Database Society, Japan Database Society, Mar. 27, 2009, vol. 7, Part 4, pp. 37-42.
Najork, Marc et al., "Breadth-First Crawling Yields High-Quality Pages", ACM, Compaq Systems Research Center, Hong Kong, 2001, pp. 114-118.
Nelson, Chris, "Use of Metadata Registries for Searching for Statistical Data", IEEE 2002, Dimension EDI Ltd., pp. 232-235, 2002.
New Zealand Examination Report in Application No. 566532, mailed Oct. 15, 2009, 2 pgs.
Non-Final Office Action in U.S. Appl. No. 11/073,831 mailed Sep. 13, 2010.
Non-Final Office Action in U.S. Appl. No. 11/874,579 mailed Jun. 22, 2010.
Numerico, T., "Search engines organization of information and Web Topology", http://www.cafm.lsbu.ac.uk/eminars/sse/numerico-6-dec-2004.pdf, Dec. 6, 2004, 32 pgs.
Official Action in U.S. Appl. No. 10/609,315 mailed Dec. 15, 2005.
Official Action in U.S. Appl. No. 10/609,315 mailed Jun. 1, 2006.
Ogilvie, P. et al., "Combining Document Representations for Known-Item Search", Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Toronto, Canada, 2003, pp. 143-150.
Okapi Similarity Measurement (Okapi), 2002, 11th International Web Conference, www2002, p. 1. *
Page, L. et al., "The PageRank Citation Ranking: Bringing Order To The Web", Internet Citation, found online at: http://citeseer.nj.nec.com/page98pagerank.html, retrieved Sep. 16, 2002, 18 pgs.
PCT International Search Report and Written Opinion in Application PCT/US2011/033125, mailed Dec. 15, 2011, 8 pgs.
PCT International Search Report in Application PCT/US06/37571, mailed Mar. 16, 2007, 10 pgs.
PCT International Search Report in PCT/US2009/036597 dated Aug. 28, 2009, 11 pgs.
PCT International Search Report, Application No. PCT/US2006/037206, mailed Jan. 16, 2007, 10 pgs.
PCT Search Report in Application PCT/US2013/022825, mailed Apr. 30, 2013, 11 pgs.
PCT Search Report in PCT/US2006/031965 mailed Jan. 11, 2007.
PCT Search Report in PCT/US2008/011894 mailed Feb. 27, 2009.
PCT Search Report in PCT/US2009/063333 dated Apr. 22, 2010.
Pera, Maria S. et al., "Using Word Similarity to Eradicate Junk Emails," Published Date: Nov. 6-8, 2007, http://delivery.acm.org/10.1145/1330000/1321581/p943-pera.pdf?key1=1321581&key2=8421170721&coll=GUIDE&dl=GUIDE&CFID=83362328&CFTOKEN=17563913, 4 pgs.
Philippines Office Action in 1-2008-500189 mailed Mar. 11, 2011, 1 page.
Philippines Official Action in 1-2008-500189 mailed Jun. 22, 2011, 1 page.
Philippines Official Action in 1-2008-500433 mailed Mar. 24, 2011, 1 page.
Phillipines Letters Patent in Application 12008500189, issued Jan. 6, 2012, 2 pgs.
Radlinski, Filip, et al.,, "Query Chains: Learning to Rank from Implicit Feedback,"http://delivery.acm.org/10.1145/1090000/1081899/p239-radlinski.pdf?key1=1081899&key2=3628533811&coll=GUIDE& CFID=27212902&CFTOKEN=53118399, KDD'05, Chicago, IL, Aug. 21-24, 2005,10 pages.
Robertson, S, Okapi at TREC-3, 1995, centre for interactive Systems Research Department of Information Science, Third Text Retrieval Conference, pp. 1-385. *
Robertson, S. et al., "Okapi at TREC-4", 1996, 24 pp.
Robertson, S. et al., "Some Simple Effective Approximations to the 2-Poisson Model for Probabilistic Weighted Retrieval", Proceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 1994, pp. 232-241.
Russian Application No. 2008105758, Notice of Allowance mailed Dec. 16, 2010, 5 pgs.
Russian Notice of Allowance in Application 2011108842, mailed Dec. 16, 2013, 7 pgs. (English translation).
Russian Notice of Allowance in Application No. 2008110731/08, mailed Oct. 25, 2010, 7 pgs.
Russian Notice of Allowance in Application No. 2010141559, mailed Jun. 27, 2013, 6 pgs.
Russian Office Action in Application 2010141559, mailed Jan. 28, 2013, 6 pgs.
Russian Official Action in 2008105758 mailed Jun. 29, 2010.
Russian Official Action in 2010141559, mailed Jan. 28, 2013, 4 pgs. (in foreign language-no English translation).
Schulz, Stefan, et al., "Indexing Medical WWW Documents by Morphemes", MEDINFO 2001 Proceedings of the 10th World Congress on Medical Informatics, Park I, IOS Press, Inc., pp. 266-270, 2001.
Second Office Action in Chinese Appln. No. 200680029645.1, dated Apr. 6, 2010.
Senecal, Sylvain, "Consumers' Decision-Making Process and Their Online Shopping Behavior: A Clickstream Analysis", Jun. 1, 2004, pp. 1600-1607.
Shamsfard, Mehrnoush, et al., "ORank: An Ontology Based System for Ranking Documents," http://www.waset.org/ijcs/v1/v1-3-30.pdf, International Journal of Computer Science, vol. 1, No. 3, Apr. 10, 2006, pp. 225-231.
Singhal, A. et al., "AT&T at TREC-9", Proceedings of the Ninth Text Retrieval Conference, NIST Special Publication 500-249, ′Online! 2001, pp. 103-105.
Singhal, A. et al., "AT&T at TREC-9", Proceedings of the Ninth Text Retrieval Conference, NIST Special Publication 500-249, 'Online! 2001, pp. 103-105.
Smyth Barry,, "Relevance at a Distance-An Investigation of Distance-Biased Personalization on the Mobile Internet", no date, pp. 1-6.
Song et al., "Exploring URL Hit Priors For Web Search", vol. 3936, Springer Berlin / Heidelberg, 2006.
South Africa Notice of Allowance in Application No. 2008/02250 mailed Jul. 23, 2009, 1 page.
Sturdy, Derek, "Squirrels and nuts: metadata and knowledge management", Business Information Review, 18(4), pp. 34-42, Dec. 2001.
Supplemental International Search Report cited in European Patent Application No. 08 840 594.9 Feb. 8, 2011, 10 pages.
Svore, Krysta M. et al., "Improving Web Spam Classification using Rank-time Features," Published Date: May 8, 2007, http://www2007.org/workshops/paper-101.pdf, 8 pgs.
Taiwan Search Report in Application 98106721, received on Sep. 2, 2014, 7 pgs.
Taiwanese Notice of Allowance in Application 95129817, mailed Jan. 29, 2013, 4 pgs.
Taiwanese Notice of Allowance in Application 98106721, mailed Jan. 30, 2015, 4 pgs.
Taiwanese Search Report in Application 95129817, mailed Oct. 19, 2012, 1 pg.
Takeda, Takaharu et al., "Multi-Document Summarization by efficient text processing", Proceedings of the FIT2007, Sixth Forum on Information Technology, vol. 2, No. E-014, pp. 165-168, Information Processing Society of Japan, Japan, Aug. 22, 2007. (not an English document).
Taylor et al., "Optimisation Methods for Ranking Functions with Multiple Parameters"-http://delivery.acm.org/10.1145/1190000/1183698/p585-taylor.pdf?key1=1183698&key2=3677533811l&coll=GUIDE&dl=GUIDE&CFID=22810237&CFTOKEN=34449120, pp. 585-593.
U.S. Appl. No. 09/493,748, Advisory Action mailed Jan. 4, 2005, 2 pgs.
U.S. Appl. No. 09/493,748, Amendment and Response filed Apr. 20, 2004, 16 pgs.
U.S. Appl. No. 09/493,748, Amendment and Response filed Oct. 12, 2004, 18 pgs.
U.S. Appl. No. 09/493,748, filed Jan. 28, 2000 entitled "Adaptive Web Crawling Using a Statistical Model".
U.S. Appl. No. 09/493,748, Final Office Action mailed Jul. 20, 2004, 14 pgs.
U.S. Appl. No. 09/493,748, Office Action mailed Sep. 25, 2003, 11 pgs.
U.S. Appl. No. 09/603,695, Advisory Action mailed Aug. 27, 2004, 3 pgs.
U.S. Appl. No. 09/603,695, Amendment and Response filed Feb. 27, 2004, 13 pgs.
U.S. Appl. No. 09/603,695, Amendment and Response filed Jul. 22, 2004, 13 pgs.
U.S. Appl. No. 09/603,695, Amendment and Response filed Nov. 5, 2004, 9 pgs.
U.S. Appl. No. 09/603,695, Final Office Action mailed May 18, 2004, 12 pgs.
U.S. Appl. No. 09/603,695, Notice of Allowance mailed Dec. 21, 2004, 8 pgs.
U.S. Appl. No. 09/603,695, Office Action mailed Nov. 7, 2003, 11 pgs.
U.S. Appl. No. 09/749,005, Amendment and Response filed Apr. 28, 2003, 12 pgs.
U.S. Appl. No. 09/749,005, Amendment and Response filed Jun. 21, 2004, 14 pgs.
U.S. Appl. No. 09/749,005, Notice of Allowance mailed Apr. 7, 2005, 4 pgs.
U.S. Appl. No. 09/749,005, Notice of Allowance mailed Aug. 30, 2004, 9 pgs.
U.S. Appl. No. 09/749,005, Notice of Allowance mailed Mar. 4, 2005, 4 pgs.
U.S. Appl. No. 09/749,005, Office Action mailed Jun. 12, 2003, 10 pgs.
U.S. Appl. No. 09/749,005, Office Action mailed Oct. 28, 2002, 12 pgs.
U.S. Appl. No. 10/609,315, Amendment and Response filed Mar. 17, 2006, 14 pgs.
U.S. Appl. No. 10/609,315, Amendment and Response filed Nov. 29, 2006, 23 pgs.
U.S. Appl. No. 10/609,315, filed Jun. 27, 2003, entitled "Normalizing Document Metadata Using Directory Services".
U.S. Appl. No. 10/609,315, Notice of Allowance mailed Jan. 24, 2007, 6 pgs.
U.S. Appl. No. 10/609,315, Notice of Allowance mailed May 30, 2007, 4 pgs.
U.S. Appl. No. 10/804,326, Advisory Action mailed Feb. 21, 2008, 3 pgs.
U.S. Appl. No. 10/804,326, Amendment and Response filed Feb. 11, 2008, 28 pgs.
U.S. Appl. No. 10/804,326, Amendment and Response filed Jun. 10, 2008, 27 pgs.
U.S. Appl. No. 10/804,326, Amendment and Response filed Mar. 16, 2007, 21 pgs.
U.S. Appl. No. 10/804,326, Amendment and Response filed Mar. 9, 2009, 8 pgs.
U.S. Appl. No. 10/804,326, Amendment and Response filed Sep. 7, 2007, 26 pgs.
U.S. Appl. No. 10/804,326, Notice of Allowance mailed May 29, 2009, 8 pgs.
U.S. Appl. No. 10/951,123, Advisory Action mailed Dec. 31, 2007, 3 pgs.
U.S. Appl. No. 10/951,123, Amendment and Response filed Apr. 25, 2007, 15 pgs.
U.S. Appl. No. 10/951,123, Amendment and Response filed Apr. 6, 2009, 18 pgs.
U.S. Appl. No. 10/951,123, Amendment and Response filed Dec. 13, 2007, 10 pgs.
U.S. Appl. No. 10/951,123, Amendment and Response filed Jan. 14, 2008, 10 pgs.
U.S. Appl. No. 10/951,123, Amendment and Response filed Sep. 17, 2008, 15 pgs.
U.S. Appl. No. 10/951,123, Final Office Action mailed Jan. 5, 2009, 23 pgs.
U.S. Appl. No. 10/951,123, Final Office Action mailed Jul. 13, 2007, 15 pgs.
U.S. Appl. No. 10/951,123, Notice of Allowance mailed Jun. 25, 2009, 5 pgs.
U.S. Appl. No. 10/951,123, Office Action mailed Jan. 25, 2007, 16 pgs.
U.S. Appl. No. 10/951,123, Office Action mailed Mar. 18, 2008, 20 pgs.
U.S. Appl. No. 10/955,462 Amendment and Response filed Aug. 8, 2007, 21 pgs.
U.S. Appl. No. 10/955,462 Amendment and Response filed Mar. 10, 2008, 17 pgs.
U.S. Appl. No. 10/955,462 Amendment and Response filed Mar. 5, 2007, 18 pgs.
U.S. Appl. No. 10/955,462 Notice of Allowance mailed Feb. 24, 2009, 7 pgs.
U.S. Appl. No. 10/955,462 Notice of Allowance mailed Jan. 25, 2010, 6 pgs.
U.S. Appl. No. 10/955,462 Notice of Allowance mailed Jun. 10, 2009, 6 pgs.
U.S. Appl. No. 10/955,462 Notice of Allowance mailed Jun. 17, 2008, 12 pgs.
U.S. Appl. No. 10/955,462 Notice of Allowance mailed Oct. 16, 2009, 7 pgs.
U.S. Appl. No. 10/955,462 Notice of Allowance mailed Sep. 23, 2008, 6 pgs.
U.S. Appl. No. 10/955,983, Amendment and Response filed Aug. 22, 2007, 13 pgs.
U.S. Appl. No. 10/955,983, Amendment and Response filed Mar. 18, 2009, 18 pgs.
U.S. Appl. No. 10/955,983, Amendment and Response filed May 13, 2008, 14 pgs.
U.S. Appl. No. 10/955,983, Amendment and Response filed Oct. 13, 2009, 12 pgs.
U.S. Appl. No. 10/955,983, Amendment and Response filed Sep. 25, 2008, 13 pgs.
U.S. Appl. No. 10/955,983, Notice of Allowance mailed Jan. 12, 2010, 10 pgs.
U.S. Appl. No. 10/955,983, Notice of Allowance mailed Jun. 4, 2010, 5 pgs.
U.S. Appl. No. 10/956,891, Advisory Action mailed Mar. 21, 2008, 3 pgs.
U.S. Appl. No. 10/956,891, Amendment and Response filed Aug. 22, 2007, 11 pgs.
U.S. Appl. No. 10/956,891, Amendment and Response filed Jun. 1, 2009, 12 pgs.
U.S. Appl. No. 10/956,891, Amendment and Response filed Mar. 3, 2008, 11 pgs.
U.S. Appl. No. 10/956,891, Amendment and Response filed May 1, 2008, 11 pgs.
U.S. Appl. No. 10/956,891, Amendment and Response filed Oct. 16, 2008, 12 pgs.
U.S. Appl. No. 10/956,891, Final Office Action filed Nov. 1, 2007, 18 pgs.
U.S. Appl. No. 10/956,891, Final Office Action mailed Dec. 31, 2008, 16 pgs.
U.S. Appl. No. 10/956,891, Notice of Allowance mailed Aug. 20, 2009, 7 pgs.
U.S. Appl. No. 10/956,891, Office Action mailed Jul. 16, 2008, 19 pgs.
U.S. Appl. No. 10/956,891, Office Action mailed Mar. 22, 2007, 15 pgs.
U.S. Appl. No. 10/959,330, Amendment and Response filed Jan. 6, 2006, 10 pgs.
U.S. Appl. No. 10/959,330, Amendment and Response filed Sep. 14, 2005, 12 pgs.
U.S. Appl. No. 10/959,330, Notice of Allowance mailed Apr. 3, 2006, 6 pgs.
U.S. Appl. No. 10/959,330, Office Action mailed Dec. 14, 2005, 6 pgs.
U.S. Appl. No. 10/959,330, Office Action mailed Jun. 27, 2005, 10 pgs.
U.S. Appl. No. 10/968,716, Amendment and Response filed Aug. 13, 2007, 6 pgs.
U.S. Appl. No. 10/968,716, Amendment and Response filed Jan. 25, 2008, 8 pgs.
U.S. Appl. No. 10/968,716, Amendment and Response filed Jun. 15, 2007, 13 pgs.
U.S. Appl. No. 10/968,716, Notice of Allowance mailed Jun. 2, 2008, 8 pgs.
U.S. Appl. No. 10/968,716, Office Action mailed Mar. 15, 2007, 13 pgs.
U.S. Appl. No. 10/968,716, Office Action mailed Oct. 26, 2007, 14 pgs.
U.S. Appl. No. 10/981,962, Advisory Action mailed Jan. 23, 2007, 3 pgs.
U.S. Appl. No. 10/981,962, Amendment and Response filed Aug. 18, 2008, 10 pgs.
U.S. Appl. No. 10/981,962, Amendment and Response filed Feb. 7, 2007, 1 pg.
U.S. Appl. No. 10/981,962, Amendment and Response filed Jul. 27, 2007, 16 pgs.
U.S. Appl. No. 10/981,962, Amendment and Response filed Jun. 27, 2006, 23 pgs.
U.S. Appl. No. 10/981,962, Amendment and Response filed Nov. 27, 2007, 10 pgs.
U.S. Appl. No. 10/981,962, Notice of Allowance mailed Aug. 20, 2009, 6 pgs.
U.S. Appl. No. 10/981,962, Notice of Allowance mailed Jan. 29, 2009, 6 pgs.
U.S. Appl. No. 10/981,962, Notice of Allowance mailed Jan. 9, 2009, 6 pgs.
U.S. Appl. No. 10/981,962, Notice of Allowance mailed May 8, 2009, 6 pgs.
U.S. Appl. No. 10/981,962, Notice of Allowance mailed Oct. 15, 2008, 6 pgs.
U.S. Appl. No. 10/981,962, Notice of Allowance mailed Sep. 11, 2008, 14 pgs.
U.S. Appl. No. 10/981,962, Office Action mailed Nov. 13, 2007, 3 pgs.
U.S. Appl. No. 11/019,091, Amendment and Response filed Dec. 20, 2007, 23 pgs.
U.S. Appl. No. 11/019,091, Amendment and Response filed Jun. 11, 2009, 12 pgs.
U.S. Appl. No. 11/019,091, Amendment and Response filed Nov. 30, 2009, 11 pgs.
U.S. Appl. No. 11/019,091, Amendment and Response filed Oct. 3, 2008, 15 pgs.
U.S. Appl. No. 11/019,091, Notice of Allowance mailed Dec. 23, 2009, 16 pgs.
U.S. Appl. No. 11/022,054, Amendment and Response filed Aug. 24, 2007, 19 pgs.
U.S. Appl. No. 11/022,054, Notice of Allowance mailed Nov. 15, 2007, 10 pgs.
U.S. Appl. No. 11/022,054, Office Action mailed Jun. 19, 2007, 19 pgs.
U.S. Appl. No. 11/073,381, Amendment and Response filed Dec. 13, 2010, 10 pgs.
U.S. Appl. No. 11/073,381, Amendment and Response filed Dec. 28, 2009, 9 pgs.
U.S. Appl. No. 11/073,381, Amendment and Response filed Dec. 9, 2008, 11 pgs.
U.S. Appl. No. 11/073,381, Amendment and Response filed Jul. 15, 2009, 10 pgs.
U.S. Appl. No. 11/073,381, Amendment and Response filed Jul. 9, 2010, 10 pgs.
U.S. Appl. No. 11/073,381, Amendment and Response filed Mar. 18, 2008, 14 pgs.
U.S. Appl. No. 11/206,286, Amendment and Response filed Jul. 22, 2009, 3 pgs.
U.S. Appl. No. 11/206,286, Amendment and Response filed Mar. 24, 2009, 13 pgs.
U.S. Appl. No. 11/206,286, Amendment and Response filed Sep. 30, 2008, 11 pgs.
U.S. Appl. No. 11/206,286, Notice of Allowance mailed Apr. 22, 2009, 9 pgs.
U.S. Appl. No. 11/231,955, filed Sep. 21, 2005, Amendment and Response filed Apr. 30, 2008, 12 pgs.
U.S. Appl. No. 11/231,955, filed Sep. 21, 2005, Amendment and Response filed Sep. 15, 2008, 16 pgs.
U.S. Appl. No. 11/231,955, filed Sep. 21, 2005, Final Office Action mailed Jun. 4, 2008, 8 pgs.
U.S. Appl. No. 11/231,955, filed Sep. 21, 2005, Notice of Allowance mailed Oct. 21, 2008, 5 pgs.
U.S. Appl. No. 11/231,955, filed Sep. 21, 2005, Office Action mailed Jan. 30, 2008, 8 pgs.
U.S. Appl. No. 11/238,906, Amendment and Response filed Feb. 26, 2009, 9 pgs.
U.S. Appl. No. 11/238,906, Amendment and Response filed Jun. 9, 2008, 10 pgs.
U.S. Appl. No. 11/238,906, Amendment and Response filed May 28, 2010, 9 pgs.
U.S. Appl. No. 11/238,906, Amendment and Response filed Sep. 1, 2009, 9 pgs.
U.S. Appl. No. 11/238,906, Notice of Allowance mailed Aug. 5, 2010, 4 pgs.
U.S. Appl. No. 11/238,906, Notice of Allowance mailed Jul. 22, 2010, 10 pgs.
U.S. Appl. No. 11/412,723, Amendment and Response filed Jun. 23, 2009, 11 pgs.
U.S. Appl. No. 11/412,723, Amendment and Response filed May 31, 2010, 11 pgs.
U.S. Appl. No. 11/412,723, Amendment and Response filed Nov. 26, 2008, 10 pgs.
U.S. Appl. No. 11/412,723, Amendment and Response filed Nov. 30, 2009, 10 pgs.
U.S. Appl. No. 11/412,723, Notice of Allowance mailed Jul. 9, 2010, 10 pgs.
U.S. Appl. No. 11/874,579, filed Oct. 18, 2007 entitled "Ranking and Providing Search Results Based in Part on a Number of Click-Through Features".
U.S. Appl. No. 11/874,579, filed Oct. 18, 2007, Amendment and Response filed Dec. 10, 2013, 17 pgs.
U.S. Appl. No. 11/874,579, filed Oct. 18, 2007, Amendment and Response filed May 16, 2011, 14 pgs.
U.S. Appl. No. 11/874,579, filed Oct. 18, 2007, Amendment and Response filed Nov. 22, 2010, 8 pgs.
U.S. Appl. No. 11/874,579, Office Action mailed Mar. 28, 2014, 30 pgs.
U.S. Appl. No. 11/874,579, Office Action mailed Sep. 10, 2013, 27 pgs.
U.S. Appl. No. 11/874,844, Amendment and Response filed Mar. 15, 2010, 16 pgs.
U.S. Appl. No. 11/874,844, filed Oct. 18, 2007 entitled "Enterprise Relevancy Ranking Using a Neural Network".
U.S. Appl. No. 11/874,844, Notice of Allowance mailed Jun. 25, 2010, 2 pgs.
U.S. Appl. No. 11/874,844, Notice of Allowance mailed May 18, 2010, 9 pgs.
U.S. Appl. No. 12/101,951, Advisory Action mailed Jun. 27, 2012, 3 pgs.
U.S. Appl. No. 12/101,951, Amendment and Response filed Dec. 3, 2010, 16 pgs.
U.S. Appl. No. 12/101,951, Amendment and Response filed Jan. 9, 2012, 10 pgs.
U.S. Appl. No. 12/101,951, Amendment and Response filed Jun. 21, 2012, 8 pgs.
U.S. Appl. No. 12/101,951, Amendment and Response filed Jun. 3, 2011, 12 pgs.
U.S. Appl. No. 12/101,951, Amendment filed Oct. 30, 2013, 8 pgs.
U.S. Appl. No. 12/101,951, Notice of Allowance mailed Apr. 25, 2014, 4 pgs.
U.S. Appl. No. 12/101,951, Notice of Allowance mailed Dec. 16, 2013, 3 pgs.
U.S. Appl. No. 12/101,951, Notice of Allowance mailed Jul. 15, 2014, 4 pgs.
U.S. Appl. No. 12/101,951, Notice of Allowance mailed Jul. 30, 2013, 5 pgs.
U.S. Appl. No. 12/101,951, Notice of Allowance mailed Mar. 26, 2014, 8 pgs.
U.S. Appl. No. 12/101,951, Notice of Allowance mailed Sep. 18, 2013, 2 pgs.
U.S. Appl. No. 12/101,951, Notice of Allowance mailed Sep. 5, 2013, 2 pgs.
U.S. Appl. No. 12/101,951, Office Action mailed Aug. 3, 2010, 26 pgs.
U.S. Appl. No. 12/101,951, Office Action mailed Feb. 24, 2012, 28 pgs.
U.S. Appl. No. 12/101,951, Office Action mailed Mar. 4, 2011, 25 pgs.
U.S. Appl. No. 12/101,951, Office Action mailed Oct. 7, 2011, 28 pgs.
U.S. Appl. No. 12/101,951, Petition and Response filed Dec. 16, 2013, 5 pgs.
U.S. Appl. No. 12/359,939, Amendment and Response filed Feb. 12, 2015, 13 pgs.
U.S. Appl. No. 12/359,939, Amendment and Response filed Jun. 27, 2014, 11 pgs.
U.S. Appl. No. 12/359,939, Amendment and Response filed Mar. 11, 2014, 10 pgs.
U.S. Appl. No. 12/359,939, Amendment and Response filed Mar. 23, 2012, 11 pgs.
U.S. Appl. No. 12/359,939, Appeal Brief filed Feb. 16, 2016, 33 pgs. pgs.
U.S. Appl. No. 12/359,939, filed Jan. 26, 2009, Amendment and Response filed Jul. 21, 2011, 8 pgs.
U.S. Appl. No. 12/359,939, filed Jan. 26, 2009, Amendment and Response filed May 23, 2011, 8 pgs.
U.S. Appl. No. 12/359,939, filed Jan. 26, 2009, Amendment and Response filed Nov. 29, 2012, 9 pgs.
U.S. Appl. No. 12/359,939, filed Jan. 26, 2009, Amendment and Response filed Oct. 26, 2012, 11 pgs.
U.S. Appl. No. 12/359,939, filed Jan. 26, 2009, Amendment and Response filed Sep. 28, 2011, 8 pgs.
U.S. Appl. No. 12/359,939, filed Jan. 26, 2009, Office Action mailed Dec. 6, 2011, 14 pgs.
U.S. Appl. No. 12/359,939, filed Jan. 26, 2009, Office Action mailed Jan. 21, 2011, 15 pgs.
U.S. Appl. No. 12/359,939, Office Action mailed Apr. 9, 2014, 18 pgs.
U.S. Appl. No. 12/359,939, Office Action mailed Aug. 4, 2015, 24 pgs.
U.S. Appl. No. 12/359,939, Office Action mailed Jan. 2, 2014, 18 pgs.
U.S. Appl. No. 12/359,939, Office Action mailed Jul. 17, 2012, 21 pgs.
U.S. Appl. No. 12/359,939, Office Action mailed Jun. 17, 2013, 19 pgs.
U.S. Appl. No. 12/359,939, Office Action mailed Nov. 6, 2014, 17 pgs.
U.S. Appl. No. 12/359,939, Office Action mailed Oct. 11, 2013, 11 pgs.
U.S. Appl. No. 12/359,939, Supplemental Amendment and Response filed Jun. 30, 2014, 8 pgs.
U.S. Appl. No. 12/359,939, Supplemental Amendment and Response filed Oct. 16, 2014, 9 pgs.
U.S. Appl. No. 12/569,028, Amendment and Response filed Aug. 2, 2013, 17 pgs.
U.S. Appl. No. 12/569,028, Amendment and Response filed Dec. 28, 2011, 8 pgs.
U.S. Appl. No. 12/569,028, Amendment and Response filed Jan. 15, 2013, 14 pgs.
U.S. Appl. No. 12/569,028, Amendment and Response filed Jan. 28, 2014, 13 pgs.
U.S. Appl. No. 12/569,028, Amendment and Response filed Jun. 27, 2012, 8 pgs.
U.S. Appl. No. 12/569,028, Notice of Allowance mailed Feb. 21, 2014, 8 pgs.
U.S. Appl. No. 12/569,028, Notice of Allowance mailed Jun. 6, 2014, 5 pgs.
U.S. Appl. No. 12/569,028, Office Action mailed Apr. 2, 2013, 21 pgs.
U.S. Appl. No. 12/569,028, Office Action mailed Aug. 28, 2013, 21 pgs.
U.S. Appl. No. 12/569,028, Office Action mailed Feb. 27, 2012, 11 pgs.
U.S. Appl. No. 12/569,028, Office Action mailed Oct. 15, 2012, 14 pgs.
U.S. Appl. No. 12/569,028, Office Action mailed Sep. 28, 2011, 14 pgs.
U.S. Appl. No. 12/791,756, Amendment and Response after Allowance filed Apr. 4, 2014, 3 pgs.
U.S. Appl. No. 12/791,756, Amendment and Response filed Apr. 30, 2012, 12 pgs.
U.S. Appl. No. 12/791,756, Amendment and Response filed Dec. 24, 2103, 19 pgs.
U.S. Appl. No. 12/791,756, Amendment and Response filed Sep. 26, 2012, 14 pgs.
U.S. Appl. No. 12/791,756, Notice of Allowance mailed Feb. 7, 2014, 10 pgs.
U.S. Appl. No. 12/791,756, Office Action mailed Jan. 31, 2012, 18 pgs.
U.S. Appl. No. 12/791,756, Office Action mailed Jun. 26, 2012, 26 pgs.
U.S. Appl. No. 12/791,756, Office Action mailed Oct. 3, 2013, 32 pgs.
U.S. Appl. No. 12/828,508 entitled "System and Method for Ranking Search Results Using Click Distance" filed Jul. 1, 2010, 29 pages.
U.S. Appl. No. 12/828,508, Amendment and Response filed Jan. 13, 2011, 11 pgs.
U.S. Appl. No. 12/828,508, Amendment and Response filed Sep. 6, 2011, 3 pgs.
U.S. Appl. No. 12/828,508, Notice of Allowance mailed Jul. 6, 2011, 8 pgs.
U.S. Appl. No. 12/828,508, Notice of Allowance mailed Mar. 31, 2011, 9 pgs.
U.S. Appl. No. 13/360,536, Amendment and Response filed Jan. 23, 2015, 13 pgs.
U.S. Appl. No. 13/360,536, Amendment and Response filed Jun. 20, 2014, 13 pgs.
U.S. Appl. No. 13/360,536, Amendment and Response filed Mar. 17, 2016, 8 pgs.
U.S. Appl. No. 13/360,536, Amendment and Response filed May 26, 2015, 14 pgs.
U.S. Appl. No. 13/360,536, Amendment and Response filed Sep. 4, 2015, 15 pgs.
U.S. Appl. No. 13/360,536, filed Jan. 27, 2012 entitled "Re-Ranking Search Results".
U.S. Appl. No. 13/360,536, Office Action mailed Feb. 26, 2015, 13 pgs.
U.S. Appl. No. 13/360,536, Office Action mailed Jun. 4, 2015, 13 pgs.
U.S. Appl. No. 13/360,536, Office Action mailed Mar. 20, 2014, 14 pgs.
U.S. Appl. No. 13/360,536, Office Action mailed Nov. 17, 2015, 12 pgs.
U.S. Appl. No. 13/360,536, Office Action mailed Sep. 23, 2014, 13 pgs.
U.S. Office Action mailed Apr. 15, 2009 in U.S. Appl. No. 11/073,381.
U.S. Office Action mailed May 19, 2009 in U.S. Appl. No. 11/238,906.
U.S. Official Action in U.S. Appl. No. 10/804,326 mailed Dec. 10, 2008.
U.S. Official Action in U.S. Appl. No. 10/804,326 mailed Dec. 11, 2007.
U.S. Official Action in U.S. Appl. No. 10/804,326 mailed Jun. 7, 2007.
U.S. Official Action in U.S. Appl. No. 10/804,326 mailed Oct. 16, 2006.
U.S. Official Action in U.S. Appl. No. 10/955,462 mailed May 11, 2007.
U.S. Official Action in U.S. Appl. No. 10/955,462 mailed Nov. 3, 2006.
U.S. Official Action in U.S. Appl. No. 10/955,462 mailed Sep. 10, 2007.
U.S. Official Action in U.S. Appl. No. 10/955,983 mailed Dec. 18, 2008.
U.S. Official Action in U.S. Appl. No. 10/955,983 mailed Jul. 21, 2008.
U.S. Official Action in U.S. Appl. No. 10/955,983 mailed Jun. 10, 2009.
U.S. Official Action in U.S. Appl. No. 10/955,983 mailed Mar. 22, 2007.
U.S. Official Action in U.S. Appl. No. 10/955,983 mailed Nov. 13, 2007.
U.S. Official Action in U.S. Appl. No. 10/981,962 mailed Apr. 30, 2007.
U.S. Official Action in U.S. Appl. No. 10/981,962 mailed Apr. 5, 2006.
U.S. Official Action in U.S. Appl. No. 10/981,962 mailed Mar. 17, 2008.
U.S. Official Action in U.S. Appl. No. 10/981,962 mailed Sep. 21, 2006.
U.S. Official Action in U.S. Appl. No. 11/019,091 mailed Apr. 3, 2008.
U.S. Official Action in U.S. Appl. No. 11/019,091 mailed Dec. 11, 2008.
U.S. Official Action in U.S. Appl. No. 11/019,091 mailed Jun. 20, 2007.
U.S. Official Action in U.S. Appl. No. 11/019,091 mailed Sep. 1, 2009.
U.S. Official Action in U.S. Appl. No. 11/073,381 mailed Apr. 12, 2010.
U.S. Official Action in U.S. Appl. No. 11/073,381 mailed Feb. 23, 2011, 30 pages.
U.S. Official Action in U.S. Appl. No. 11/073,381 mailed Jul. 10, 2008.
U.S. Official Action in U.S. Appl. No. 11/073,381 mailed Sep. 18, 2007.
U.S. Official Action in U.S. Appl. No. 11/073,381 mailed Sep. 29, 2009.
U.S. Official Action in U.S. Appl. No. 11/206,286 mailed Dec. 24, 2008.
U.S. Official Action in U.S. Appl. No. 11/206,286 mailed Jul. 14, 2008.
U.S. Official Action in U.S. Appl. No. 11/238,906 mailed Jan. 8, 2008.
U.S. Official Action in U.S. Appl. No. 11/238,906 mailed Sep. 16, 2008.
U.S. Official Action in U.S. Appl. No. 11/412,723 mailed Mar. 6, 2009.
U.S. Official Action in U.S. Appl. No. 11/412,723 mailed May 28, 2008.
U.S. Official Action in U.S. Appl. No. 11/412,723 mailed Sep. 3, 2009.
U.S. Official Non-Final Action in U.S. Appl. No. 12/828,508 mailed Aug. 13, 2010.
US Official Final Action mailed Dec. 18, 2009 in U.S. Appl. No. 11/238,906.
US Official Final Action mailed Mar. 11, 2010 in U.S. Appl. No. 11/412,723.
US Official Non-Final Action mailed Nov. 13, 2009 in U.S. Appl. No. 11/874,844.
US Restriction Requirement in U.S. Appl. No. 10/804,326 mailed Aug. 20, 2008, 5 pgs.
US Restriction Requirement in U.S. Appl. No. 11/231,955 mailed Nov. 30, 2007, 6 pgs.
US Restriction Requirement in U.S. Appl. No. 11/231,955 mailed Oct. 23, 2007, 6 pgs.
Utiyama, Masao et al., "Implementation of an IR package", IPSJ SIG Notes, vol. 2001, No. 74 (2001-FI-63-8), pp. 57-64, Information Processing Society of Japan, Japan, Jul. 25, 2001. (not an English document).
Voorhees, E., "Overview of TREC 2002", Gaithersburg, Maryland, Nov. 19-22, 15 pp.
Web Page "Reuters: Reuters Corpus", http://about.reuter.com/researchandstandards/corpus/, viewed Mar. 18, 2004.
Wen, Jl-Rong, "Query Clustering Using User Logs", Jan. 2002, pp. 59-81.
Westerveld, T. et al., "Retrieving Web pages using Content, Links, URLs and Anchors", Proceedings of the Tenth Text Retrieval Conference, NIST Special Publication, ′Online! Oct. 2001, pp. 1-10.
Westerveld, T. et al., "Retrieving Web pages using Content, Links, URLs and Anchors", Proceedings of the Tenth Text Retrieval Conference, NIST Special Publication, 'Online! Oct. 2001, pp. 1-10.
Wilkinson, R., "Effective Retrieval of Structured Documents", Annual ACM Conference on Research and Development, 1994, 7 pp.
Xue, Gui-Rong, et al., "Optimizing Web Search Using Web Click-Through Data," http://people.cs.vt.edu/~xwensi/Publication/p118-xue.pdf, CIKM'04, Nov. 8-13, 2004, 9 pages.
Xue, Gui-Rong, et al., "Optimizing Web Search Using Web Click-Through Data," http://people.cs.vt.edu/˜xwensi/Publication/p118-xue.pdf, CIKM'04, Nov. 8-13, 2004, 9 pages.
Yi, Jeonghe,e et al., "Metadata Based Web Mining for Topic-Specific Information Gathering", IEEE, pp. 359-368, 2000.
Yi, Jeonghee, et al., "Using Metadata to Enhance Web Information Gathering", D.Suciu and G. Vossen (eds.): WebDB 2000, LNCS 1997, pp. 38-57, 2001.
Yuwono, Budi and Lee, Dik L., "Search and Ranking Algorithms for Locating Resources on the World Wide Web", IEEE, 1996, pp. 164-170.
Zamir, O. et al., "Grouper: A Dynamic Clustering Interface to Web Search Results", Computer Networks (Amsterdam, Netherlands: 1999), 31(11-16): 1361-1374, 1999.

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160162467A1 (en) * 2014-12-09 2016-06-09 Idibon, Inc. Methods and systems for language-agnostic machine learning in natural language processing using feature extraction

Also Published As

Publication number Publication date Type
KR101683311B1 (en) 2016-12-06 grant
JP5620913B2 (en) 2014-09-26 grant
JP2013510343A (en) 2013-03-21 application
EP2329411A4 (en) 2016-04-06 application
EP2329411A2 (en) 2011-06-08 application
WO2010031085A3 (en) 2010-07-08 application
RU2011108842A (en) 2012-09-20 application
WO2010031085A2 (en) 2010-03-18 application
RU2517271C2 (en) 2014-05-27 grant
KR20120089560A (en) 2012-08-13 application
US20090106235A1 (en) 2009-04-23 application

Similar Documents

Publication Publication Date Title
Yanbe et al. Can social bookmarking enhance search in the web?
Qin et al. LETOR: A benchmark collection for research on learning to rank for information retrieval
US7117206B1 (en) Method for ranking hyperlinked pages using content and connectivity analysis
US7565345B2 (en) Integration of multiple query revision models
US7392250B1 (en) Discovering interestingness in faceted search
US8086605B2 (en) Search engine with augmented relevance ranking by community participation
Perkowitz et al. Towards adaptive web sites: Conceptual framework and case study
Fagin et al. Searching the workplace web
US20030120653A1 (en) Trainable internet search engine and methods of using
US7765178B1 (en) Search ranking estimation
US20100010989A1 (en) Method for Efficiently Supporting Interactive, Fuzzy Search on Structured Data
Wu et al. Query selection techniques for efficient crawling of structured web sources
US20060074903A1 (en) System and method for ranking search results using click distance
US20040002973A1 (en) Automatically ranking answers to database queries
US7783630B1 (en) Tuning of relevancy ranking for federated search
US7039631B1 (en) System and method for providing search results with configurable scoring formula
Collins-Thompson et al. Personalizing web search results by reading level
US7493312B2 (en) Media agent
US20060155751A1 (en) System and method for document analysis, processing and information extraction
US20060143254A1 (en) System and method for using anchor text as training data for classifier-based search systems
US8260774B1 (en) Personalization search engine
Dmitriev et al. Using annotations in enterprise search
US20100299343A1 (en) Identifying Task Groups for Organizing Search Results
US8145636B1 (en) Classifying text into hierarchical categories
US20120278321A1 (en) Visualization of concepts within a collection of information

Legal Events

Date Code Title Description
AS Assignment

Owner name: MICROSOFT CORPORATION, WASHINGTON

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:TANKOVICH, VLADIMIR;MEYERZON, DMITRIY;TAYLOR, MICHAEL JAMES;REEL/FRAME:021533/0008;SIGNING DATES FROM 20080903 TO 20080904

Owner name: MICROSOFT CORPORATION, WASHINGTON

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:TANKOVICH, VLADIMIR;MEYERZON, DMITRIY;TAYLOR, MICHAEL JAMES;SIGNING DATES FROM 20080903 TO 20080904;REEL/FRAME:021533/0008

AS Assignment

Owner name: MICROSOFT TECHNOLOGY LICENSING, LLC, WASHINGTON

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:MICROSOFT CORPORATION;REEL/FRAME:034564/0001

Effective date: 20141014